| File: | jdk/src/java.desktop/share/native/libjavajpeg/jquant2.c |
| Warning: | line 536, column 66 Division by zero |
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| 1 | /* | |||
| 2 | * reserved comment block | |||
| 3 | * DO NOT REMOVE OR ALTER! | |||
| 4 | */ | |||
| 5 | /* | |||
| 6 | * jquant2.c | |||
| 7 | * | |||
| 8 | * Copyright (C) 1991-1996, Thomas G. Lane. | |||
| 9 | * This file is part of the Independent JPEG Group's software. | |||
| 10 | * For conditions of distribution and use, see the accompanying README file. | |||
| 11 | * | |||
| 12 | * This file contains 2-pass color quantization (color mapping) routines. | |||
| 13 | * These routines provide selection of a custom color map for an image, | |||
| 14 | * followed by mapping of the image to that color map, with optional | |||
| 15 | * Floyd-Steinberg dithering. | |||
| 16 | * It is also possible to use just the second pass to map to an arbitrary | |||
| 17 | * externally-given color map. | |||
| 18 | * | |||
| 19 | * Note: ordered dithering is not supported, since there isn't any fast | |||
| 20 | * way to compute intercolor distances; it's unclear that ordered dither's | |||
| 21 | * fundamental assumptions even hold with an irregularly spaced color map. | |||
| 22 | */ | |||
| 23 | ||||
| 24 | #define JPEG_INTERNALS | |||
| 25 | #include "jinclude.h" | |||
| 26 | #include "jpeglib.h" | |||
| 27 | ||||
| 28 | #ifdef QUANT_2PASS_SUPPORTED | |||
| 29 | ||||
| 30 | ||||
| 31 | /* | |||
| 32 | * This module implements the well-known Heckbert paradigm for color | |||
| 33 | * quantization. Most of the ideas used here can be traced back to | |||
| 34 | * Heckbert's seminal paper | |||
| 35 | * Heckbert, Paul. "Color Image Quantization for Frame Buffer Display", | |||
| 36 | * Proc. SIGGRAPH '82, Computer Graphics v.16 #3 (July 1982), pp 297-304. | |||
| 37 | * | |||
| 38 | * In the first pass over the image, we accumulate a histogram showing the | |||
| 39 | * usage count of each possible color. To keep the histogram to a reasonable | |||
| 40 | * size, we reduce the precision of the input; typical practice is to retain | |||
| 41 | * 5 or 6 bits per color, so that 8 or 4 different input values are counted | |||
| 42 | * in the same histogram cell. | |||
| 43 | * | |||
| 44 | * Next, the color-selection step begins with a box representing the whole | |||
| 45 | * color space, and repeatedly splits the "largest" remaining box until we | |||
| 46 | * have as many boxes as desired colors. Then the mean color in each | |||
| 47 | * remaining box becomes one of the possible output colors. | |||
| 48 | * | |||
| 49 | * The second pass over the image maps each input pixel to the closest output | |||
| 50 | * color (optionally after applying a Floyd-Steinberg dithering correction). | |||
| 51 | * This mapping is logically trivial, but making it go fast enough requires | |||
| 52 | * considerable care. | |||
| 53 | * | |||
| 54 | * Heckbert-style quantizers vary a good deal in their policies for choosing | |||
| 55 | * the "largest" box and deciding where to cut it. The particular policies | |||
| 56 | * used here have proved out well in experimental comparisons, but better ones | |||
| 57 | * may yet be found. | |||
| 58 | * | |||
| 59 | * In earlier versions of the IJG code, this module quantized in YCbCr color | |||
| 60 | * space, processing the raw upsampled data without a color conversion step. | |||
| 61 | * This allowed the color conversion math to be done only once per colormap | |||
| 62 | * entry, not once per pixel. However, that optimization precluded other | |||
| 63 | * useful optimizations (such as merging color conversion with upsampling) | |||
| 64 | * and it also interfered with desired capabilities such as quantizing to an | |||
| 65 | * externally-supplied colormap. We have therefore abandoned that approach. | |||
| 66 | * The present code works in the post-conversion color space, typically RGB. | |||
| 67 | * | |||
| 68 | * To improve the visual quality of the results, we actually work in scaled | |||
| 69 | * RGB space, giving G distances more weight than R, and R in turn more than | |||
| 70 | * B. To do everything in integer math, we must use integer scale factors. | |||
| 71 | * The 2/3/1 scale factors used here correspond loosely to the relative | |||
| 72 | * weights of the colors in the NTSC grayscale equation. | |||
| 73 | * If you want to use this code to quantize a non-RGB color space, you'll | |||
| 74 | * probably need to change these scale factors. | |||
| 75 | */ | |||
| 76 | ||||
| 77 | #define R_SCALE2 2 /* scale R distances by this much */ | |||
| 78 | #define G_SCALE3 3 /* scale G distances by this much */ | |||
| 79 | #define B_SCALE1 1 /* and B by this much */ | |||
| 80 | ||||
| 81 | /* Relabel R/G/B as components 0/1/2, respecting the RGB ordering defined | |||
| 82 | * in jmorecfg.h. As the code stands, it will do the right thing for R,G,B | |||
| 83 | * and B,G,R orders. If you define some other weird order in jmorecfg.h, | |||
| 84 | * you'll get compile errors until you extend this logic. In that case | |||
| 85 | * you'll probably want to tweak the histogram sizes too. | |||
| 86 | */ | |||
| 87 | ||||
| 88 | #if RGB_RED0 == 0 | |||
| 89 | #define C0_SCALE2 R_SCALE2 | |||
| 90 | #endif | |||
| 91 | #if RGB_BLUE2 == 0 | |||
| 92 | #define C0_SCALE2 B_SCALE1 | |||
| 93 | #endif | |||
| 94 | #if RGB_GREEN1 == 1 | |||
| 95 | #define C1_SCALE3 G_SCALE3 | |||
| 96 | #endif | |||
| 97 | #if RGB_RED0 == 2 | |||
| 98 | #define C2_SCALE1 R_SCALE2 | |||
| 99 | #endif | |||
| 100 | #if RGB_BLUE2 == 2 | |||
| 101 | #define C2_SCALE1 B_SCALE1 | |||
| 102 | #endif | |||
| 103 | ||||
| 104 | ||||
| 105 | /* | |||
| 106 | * First we have the histogram data structure and routines for creating it. | |||
| 107 | * | |||
| 108 | * The number of bits of precision can be adjusted by changing these symbols. | |||
| 109 | * We recommend keeping 6 bits for G and 5 each for R and B. | |||
| 110 | * If you have plenty of memory and cycles, 6 bits all around gives marginally | |||
| 111 | * better results; if you are short of memory, 5 bits all around will save | |||
| 112 | * some space but degrade the results. | |||
| 113 | * To maintain a fully accurate histogram, we'd need to allocate a "long" | |||
| 114 | * (preferably unsigned long) for each cell. In practice this is overkill; | |||
| 115 | * we can get by with 16 bits per cell. Few of the cell counts will overflow, | |||
| 116 | * and clamping those that do overflow to the maximum value will give close- | |||
| 117 | * enough results. This reduces the recommended histogram size from 256Kb | |||
| 118 | * to 128Kb, which is a useful savings on PC-class machines. | |||
| 119 | * (In the second pass the histogram space is re-used for pixel mapping data; | |||
| 120 | * in that capacity, each cell must be able to store zero to the number of | |||
| 121 | * desired colors. 16 bits/cell is plenty for that too.) | |||
| 122 | * Since the JPEG code is intended to run in small memory model on 80x86 | |||
| 123 | * machines, we can't just allocate the histogram in one chunk. Instead | |||
| 124 | * of a true 3-D array, we use a row of pointers to 2-D arrays. Each | |||
| 125 | * pointer corresponds to a C0 value (typically 2^5 = 32 pointers) and | |||
| 126 | * each 2-D array has 2^6*2^5 = 2048 or 2^6*2^6 = 4096 entries. Note that | |||
| 127 | * on 80x86 machines, the pointer row is in near memory but the actual | |||
| 128 | * arrays are in far memory (same arrangement as we use for image arrays). | |||
| 129 | */ | |||
| 130 | ||||
| 131 | #define MAXNUMCOLORS(255 +1) (MAXJSAMPLE255+1) /* maximum size of colormap */ | |||
| 132 | ||||
| 133 | /* These will do the right thing for either R,G,B or B,G,R color order, | |||
| 134 | * but you may not like the results for other color orders. | |||
| 135 | */ | |||
| 136 | #define HIST_C0_BITS5 5 /* bits of precision in R/B histogram */ | |||
| 137 | #define HIST_C1_BITS6 6 /* bits of precision in G histogram */ | |||
| 138 | #define HIST_C2_BITS5 5 /* bits of precision in B/R histogram */ | |||
| 139 | ||||
| 140 | /* Number of elements along histogram axes. */ | |||
| 141 | #define HIST_C0_ELEMS(1<<5) (1<<HIST_C0_BITS5) | |||
| 142 | #define HIST_C1_ELEMS(1<<6) (1<<HIST_C1_BITS6) | |||
| 143 | #define HIST_C2_ELEMS(1<<5) (1<<HIST_C2_BITS5) | |||
| 144 | ||||
| 145 | /* These are the amounts to shift an input value to get a histogram index. */ | |||
| 146 | #define C0_SHIFT(8 -5) (BITS_IN_JSAMPLE8-HIST_C0_BITS5) | |||
| 147 | #define C1_SHIFT(8 -6) (BITS_IN_JSAMPLE8-HIST_C1_BITS6) | |||
| 148 | #define C2_SHIFT(8 -5) (BITS_IN_JSAMPLE8-HIST_C2_BITS5) | |||
| 149 | ||||
| 150 | ||||
| 151 | typedef UINT16 histcell; /* histogram cell; prefer an unsigned type */ | |||
| 152 | ||||
| 153 | typedef histcell FAR * histptr; /* for pointers to histogram cells */ | |||
| 154 | ||||
| 155 | typedef histcell hist1d[HIST_C2_ELEMS(1<<5)]; /* typedefs for the array */ | |||
| 156 | typedef hist1d FAR * hist2d; /* type for the 2nd-level pointers */ | |||
| 157 | typedef hist2d * hist3d; /* type for top-level pointer */ | |||
| 158 | ||||
| 159 | ||||
| 160 | /* Declarations for Floyd-Steinberg dithering. | |||
| 161 | * | |||
| 162 | * Errors are accumulated into the array fserrors[], at a resolution of | |||
| 163 | * 1/16th of a pixel count. The error at a given pixel is propagated | |||
| 164 | * to its not-yet-processed neighbors using the standard F-S fractions, | |||
| 165 | * ... (here) 7/16 | |||
| 166 | * 3/16 5/16 1/16 | |||
| 167 | * We work left-to-right on even rows, right-to-left on odd rows. | |||
| 168 | * | |||
| 169 | * We can get away with a single array (holding one row's worth of errors) | |||
| 170 | * by using it to store the current row's errors at pixel columns not yet | |||
| 171 | * processed, but the next row's errors at columns already processed. We | |||
| 172 | * need only a few extra variables to hold the errors immediately around the | |||
| 173 | * current column. (If we are lucky, those variables are in registers, but | |||
| 174 | * even if not, they're probably cheaper to access than array elements are.) | |||
| 175 | * | |||
| 176 | * The fserrors[] array has (#columns + 2) entries; the extra entry at | |||
| 177 | * each end saves us from special-casing the first and last pixels. | |||
| 178 | * Each entry is three values long, one value for each color component. | |||
| 179 | * | |||
| 180 | * Note: on a wide image, we might not have enough room in a PC's near data | |||
| 181 | * segment to hold the error array; so it is allocated with alloc_large. | |||
| 182 | */ | |||
| 183 | ||||
| 184 | #if BITS_IN_JSAMPLE8 == 8 | |||
| 185 | typedef INT16 FSERROR; /* 16 bits should be enough */ | |||
| 186 | typedef int LOCFSERROR; /* use 'int' for calculation temps */ | |||
| 187 | #else | |||
| 188 | typedef INT32 FSERROR; /* may need more than 16 bits */ | |||
| 189 | typedef INT32 LOCFSERROR; /* be sure calculation temps are big enough */ | |||
| 190 | #endif | |||
| 191 | ||||
| 192 | typedef FSERROR FAR *FSERRPTR; /* pointer to error array (in FAR storage!) */ | |||
| 193 | ||||
| 194 | ||||
| 195 | /* Private subobject */ | |||
| 196 | ||||
| 197 | typedef struct { | |||
| 198 | struct jpeg_color_quantizer pub; /* public fields */ | |||
| 199 | ||||
| 200 | /* Space for the eventually created colormap is stashed here */ | |||
| 201 | JSAMPARRAY sv_colormap; /* colormap allocated at init time */ | |||
| 202 | int desired; /* desired # of colors = size of colormap */ | |||
| 203 | ||||
| 204 | /* Variables for accumulating image statistics */ | |||
| 205 | hist3d histogram; /* pointer to the histogram */ | |||
| 206 | ||||
| 207 | boolean needs_zeroed; /* TRUE if next pass must zero histogram */ | |||
| 208 | ||||
| 209 | /* Variables for Floyd-Steinberg dithering */ | |||
| 210 | FSERRPTR fserrors; /* accumulated errors */ | |||
| 211 | boolean on_odd_row; /* flag to remember which row we are on */ | |||
| 212 | int * error_limiter; /* table for clamping the applied error */ | |||
| 213 | } my_cquantizer; | |||
| 214 | ||||
| 215 | typedef my_cquantizer * my_cquantize_ptr; | |||
| 216 | ||||
| 217 | ||||
| 218 | /* | |||
| 219 | * Prescan some rows of pixels. | |||
| 220 | * In this module the prescan simply updates the histogram, which has been | |||
| 221 | * initialized to zeroes by start_pass. | |||
| 222 | * An output_buf parameter is required by the method signature, but no data | |||
| 223 | * is actually output (in fact the buffer controller is probably passing a | |||
| 224 | * NULL pointer). | |||
| 225 | */ | |||
| 226 | ||||
| 227 | METHODDEF(void)static void | |||
| 228 | prescan_quantize (j_decompress_ptr cinfo, JSAMPARRAY input_buf, | |||
| 229 | JSAMPARRAY output_buf, int num_rows) | |||
| 230 | { | |||
| 231 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 232 | register JSAMPROW ptr; | |||
| 233 | register histptr histp; | |||
| 234 | register hist3d histogram = cquantize->histogram; | |||
| 235 | int row; | |||
| 236 | JDIMENSION col; | |||
| 237 | JDIMENSION width = cinfo->output_width; | |||
| 238 | ||||
| 239 | for (row = 0; row < num_rows; row++) { | |||
| 240 | ptr = input_buf[row]; | |||
| 241 | for (col = width; col > 0; col--) { | |||
| 242 | /* get pixel value and index into the histogram */ | |||
| 243 | histp = & histogram[GETJSAMPLE(ptr[0])((int) (ptr[0])) >> C0_SHIFT(8 -5)] | |||
| 244 | [GETJSAMPLE(ptr[1])((int) (ptr[1])) >> C1_SHIFT(8 -6)] | |||
| 245 | [GETJSAMPLE(ptr[2])((int) (ptr[2])) >> C2_SHIFT(8 -5)]; | |||
| 246 | /* increment, check for overflow and undo increment if so. */ | |||
| 247 | if (++(*histp) <= 0) | |||
| 248 | (*histp)--; | |||
| 249 | ptr += 3; | |||
| 250 | } | |||
| 251 | } | |||
| 252 | } | |||
| 253 | ||||
| 254 | ||||
| 255 | /* | |||
| 256 | * Next we have the really interesting routines: selection of a colormap | |||
| 257 | * given the completed histogram. | |||
| 258 | * These routines work with a list of "boxes", each representing a rectangular | |||
| 259 | * subset of the input color space (to histogram precision). | |||
| 260 | */ | |||
| 261 | ||||
| 262 | typedef struct { | |||
| 263 | /* The bounds of the box (inclusive); expressed as histogram indexes */ | |||
| 264 | int c0min, c0max; | |||
| 265 | int c1min, c1max; | |||
| 266 | int c2min, c2max; | |||
| 267 | /* The volume (actually 2-norm) of the box */ | |||
| 268 | INT32 volume; | |||
| 269 | /* The number of nonzero histogram cells within this box */ | |||
| 270 | long colorcount; | |||
| 271 | } box; | |||
| 272 | ||||
| 273 | typedef box * boxptr; | |||
| 274 | ||||
| 275 | ||||
| 276 | LOCAL(boxptr)static boxptr | |||
| 277 | find_biggest_color_pop (boxptr boxlist, int numboxes) | |||
| 278 | /* Find the splittable box with the largest color population */ | |||
| 279 | /* Returns NULL if no splittable boxes remain */ | |||
| 280 | { | |||
| 281 | register boxptr boxp; | |||
| 282 | register int i; | |||
| 283 | register long maxc = 0; | |||
| 284 | boxptr which = NULL((void*)0); | |||
| 285 | ||||
| 286 | for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) { | |||
| 287 | if (boxp->colorcount > maxc && boxp->volume > 0) { | |||
| 288 | which = boxp; | |||
| 289 | maxc = boxp->colorcount; | |||
| 290 | } | |||
| 291 | } | |||
| 292 | return which; | |||
| 293 | } | |||
| 294 | ||||
| 295 | ||||
| 296 | LOCAL(boxptr)static boxptr | |||
| 297 | find_biggest_volume (boxptr boxlist, int numboxes) | |||
| 298 | /* Find the splittable box with the largest (scaled) volume */ | |||
| 299 | /* Returns NULL if no splittable boxes remain */ | |||
| 300 | { | |||
| 301 | register boxptr boxp; | |||
| 302 | register int i; | |||
| 303 | register INT32 maxv = 0; | |||
| 304 | boxptr which = NULL((void*)0); | |||
| 305 | ||||
| 306 | for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++) { | |||
| 307 | if (boxp->volume > maxv) { | |||
| 308 | which = boxp; | |||
| 309 | maxv = boxp->volume; | |||
| 310 | } | |||
| 311 | } | |||
| 312 | return which; | |||
| 313 | } | |||
| 314 | ||||
| 315 | ||||
| 316 | LOCAL(void)static void | |||
| 317 | update_box (j_decompress_ptr cinfo, boxptr boxp) | |||
| 318 | /* Shrink the min/max bounds of a box to enclose only nonzero elements, */ | |||
| 319 | /* and recompute its volume and population */ | |||
| 320 | { | |||
| 321 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 322 | hist3d histogram = cquantize->histogram; | |||
| 323 | histptr histp; | |||
| 324 | int c0,c1,c2; | |||
| 325 | int c0min,c0max,c1min,c1max,c2min,c2max; | |||
| 326 | INT32 dist0,dist1,dist2; | |||
| 327 | long ccount; | |||
| 328 | ||||
| 329 | c0min = boxp->c0min; c0max = boxp->c0max; | |||
| 330 | c1min = boxp->c1min; c1max = boxp->c1max; | |||
| 331 | c2min = boxp->c2min; c2max = boxp->c2max; | |||
| 332 | ||||
| 333 | if (c0max > c0min) | |||
| 334 | for (c0 = c0min; c0 <= c0max; c0++) | |||
| 335 | for (c1 = c1min; c1 <= c1max; c1++) { | |||
| 336 | histp = & histogram[c0][c1][c2min]; | |||
| 337 | for (c2 = c2min; c2 <= c2max; c2++) | |||
| 338 | if (*histp++ != 0) { | |||
| 339 | boxp->c0min = c0min = c0; | |||
| 340 | goto have_c0min; | |||
| 341 | } | |||
| 342 | } | |||
| 343 | have_c0min: | |||
| 344 | if (c0max > c0min) | |||
| 345 | for (c0 = c0max; c0 >= c0min; c0--) | |||
| 346 | for (c1 = c1min; c1 <= c1max; c1++) { | |||
| 347 | histp = & histogram[c0][c1][c2min]; | |||
| 348 | for (c2 = c2min; c2 <= c2max; c2++) | |||
| 349 | if (*histp++ != 0) { | |||
| 350 | boxp->c0max = c0max = c0; | |||
| 351 | goto have_c0max; | |||
| 352 | } | |||
| 353 | } | |||
| 354 | have_c0max: | |||
| 355 | if (c1max > c1min) | |||
| 356 | for (c1 = c1min; c1 <= c1max; c1++) | |||
| 357 | for (c0 = c0min; c0 <= c0max; c0++) { | |||
| 358 | histp = & histogram[c0][c1][c2min]; | |||
| 359 | for (c2 = c2min; c2 <= c2max; c2++) | |||
| 360 | if (*histp++ != 0) { | |||
| 361 | boxp->c1min = c1min = c1; | |||
| 362 | goto have_c1min; | |||
| 363 | } | |||
| 364 | } | |||
| 365 | have_c1min: | |||
| 366 | if (c1max > c1min) | |||
| 367 | for (c1 = c1max; c1 >= c1min; c1--) | |||
| 368 | for (c0 = c0min; c0 <= c0max; c0++) { | |||
| 369 | histp = & histogram[c0][c1][c2min]; | |||
| 370 | for (c2 = c2min; c2 <= c2max; c2++) | |||
| 371 | if (*histp++ != 0) { | |||
| 372 | boxp->c1max = c1max = c1; | |||
| 373 | goto have_c1max; | |||
| 374 | } | |||
| 375 | } | |||
| 376 | have_c1max: | |||
| 377 | if (c2max > c2min) | |||
| 378 | for (c2 = c2min; c2 <= c2max; c2++) | |||
| 379 | for (c0 = c0min; c0 <= c0max; c0++) { | |||
| 380 | histp = & histogram[c0][c1min][c2]; | |||
| 381 | for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS(1<<5)) | |||
| 382 | if (*histp != 0) { | |||
| 383 | boxp->c2min = c2min = c2; | |||
| 384 | goto have_c2min; | |||
| 385 | } | |||
| 386 | } | |||
| 387 | have_c2min: | |||
| 388 | if (c2max > c2min) | |||
| 389 | for (c2 = c2max; c2 >= c2min; c2--) | |||
| 390 | for (c0 = c0min; c0 <= c0max; c0++) { | |||
| 391 | histp = & histogram[c0][c1min][c2]; | |||
| 392 | for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS(1<<5)) | |||
| 393 | if (*histp != 0) { | |||
| 394 | boxp->c2max = c2max = c2; | |||
| 395 | goto have_c2max; | |||
| 396 | } | |||
| 397 | } | |||
| 398 | have_c2max: | |||
| 399 | ||||
| 400 | /* Update box volume. | |||
| 401 | * We use 2-norm rather than real volume here; this biases the method | |||
| 402 | * against making long narrow boxes, and it has the side benefit that | |||
| 403 | * a box is splittable iff norm > 0. | |||
| 404 | * Since the differences are expressed in histogram-cell units, | |||
| 405 | * we have to shift back to JSAMPLE units to get consistent distances; | |||
| 406 | * after which, we scale according to the selected distance scale factors. | |||
| 407 | */ | |||
| 408 | dist0 = ((c0max - c0min) << C0_SHIFT(8 -5)) * C0_SCALE2; | |||
| 409 | dist1 = ((c1max - c1min) << C1_SHIFT(8 -6)) * C1_SCALE3; | |||
| 410 | dist2 = ((c2max - c2min) << C2_SHIFT(8 -5)) * C2_SCALE1; | |||
| 411 | boxp->volume = dist0*dist0 + dist1*dist1 + dist2*dist2; | |||
| 412 | ||||
| 413 | /* Now scan remaining volume of box and compute population */ | |||
| 414 | ccount = 0; | |||
| 415 | for (c0 = c0min; c0 <= c0max; c0++) | |||
| 416 | for (c1 = c1min; c1 <= c1max; c1++) { | |||
| 417 | histp = & histogram[c0][c1][c2min]; | |||
| 418 | for (c2 = c2min; c2 <= c2max; c2++, histp++) | |||
| 419 | if (*histp != 0) { | |||
| 420 | ccount++; | |||
| 421 | } | |||
| 422 | } | |||
| 423 | boxp->colorcount = ccount; | |||
| 424 | } | |||
| 425 | ||||
| 426 | ||||
| 427 | LOCAL(int)static int | |||
| 428 | median_cut (j_decompress_ptr cinfo, boxptr boxlist, int numboxes, | |||
| 429 | int desired_colors) | |||
| 430 | /* Repeatedly select and split the largest box until we have enough boxes */ | |||
| 431 | { | |||
| 432 | int n,lb; | |||
| 433 | int c0,c1,c2,cmax; | |||
| 434 | register boxptr b1,b2; | |||
| 435 | ||||
| 436 | while (numboxes < desired_colors) { | |||
| 437 | /* Select box to split. | |||
| 438 | * Current algorithm: by population for first half, then by volume. | |||
| 439 | */ | |||
| 440 | if (numboxes*2 <= desired_colors) { | |||
| 441 | b1 = find_biggest_color_pop(boxlist, numboxes); | |||
| 442 | } else { | |||
| 443 | b1 = find_biggest_volume(boxlist, numboxes); | |||
| 444 | } | |||
| 445 | if (b1 == NULL((void*)0)) /* no splittable boxes left! */ | |||
| 446 | break; | |||
| 447 | b2 = &boxlist[numboxes]; /* where new box will go */ | |||
| 448 | /* Copy the color bounds to the new box. */ | |||
| 449 | b2->c0max = b1->c0max; b2->c1max = b1->c1max; b2->c2max = b1->c2max; | |||
| 450 | b2->c0min = b1->c0min; b2->c1min = b1->c1min; b2->c2min = b1->c2min; | |||
| 451 | /* Choose which axis to split the box on. | |||
| 452 | * Current algorithm: longest scaled axis. | |||
| 453 | * See notes in update_box about scaling distances. | |||
| 454 | */ | |||
| 455 | c0 = ((b1->c0max - b1->c0min) << C0_SHIFT(8 -5)) * C0_SCALE2; | |||
| 456 | c1 = ((b1->c1max - b1->c1min) << C1_SHIFT(8 -6)) * C1_SCALE3; | |||
| 457 | c2 = ((b1->c2max - b1->c2min) << C2_SHIFT(8 -5)) * C2_SCALE1; | |||
| 458 | /* We want to break any ties in favor of green, then red, blue last. | |||
| 459 | * This code does the right thing for R,G,B or B,G,R color orders only. | |||
| 460 | */ | |||
| 461 | #if RGB_RED0 == 0 | |||
| 462 | cmax = c1; n = 1; | |||
| 463 | if (c0 > cmax) { cmax = c0; n = 0; } | |||
| 464 | if (c2 > cmax) { n = 2; } | |||
| 465 | #else | |||
| 466 | cmax = c1; n = 1; | |||
| 467 | if (c2 > cmax) { cmax = c2; n = 2; } | |||
| 468 | if (c0 > cmax) { n = 0; } | |||
| 469 | #endif | |||
| 470 | /* Choose split point along selected axis, and update box bounds. | |||
| 471 | * Current algorithm: split at halfway point. | |||
| 472 | * (Since the box has been shrunk to minimum volume, | |||
| 473 | * any split will produce two nonempty subboxes.) | |||
| 474 | * Note that lb value is max for lower box, so must be < old max. | |||
| 475 | */ | |||
| 476 | switch (n) { | |||
| 477 | case 0: | |||
| 478 | lb = (b1->c0max + b1->c0min) / 2; | |||
| 479 | b1->c0max = lb; | |||
| 480 | b2->c0min = lb+1; | |||
| 481 | break; | |||
| 482 | case 1: | |||
| 483 | lb = (b1->c1max + b1->c1min) / 2; | |||
| 484 | b1->c1max = lb; | |||
| 485 | b2->c1min = lb+1; | |||
| 486 | break; | |||
| 487 | case 2: | |||
| 488 | lb = (b1->c2max + b1->c2min) / 2; | |||
| 489 | b1->c2max = lb; | |||
| 490 | b2->c2min = lb+1; | |||
| 491 | break; | |||
| 492 | } | |||
| 493 | /* Update stats for boxes */ | |||
| 494 | update_box(cinfo, b1); | |||
| 495 | update_box(cinfo, b2); | |||
| 496 | numboxes++; | |||
| 497 | } | |||
| 498 | return numboxes; | |||
| 499 | } | |||
| 500 | ||||
| 501 | ||||
| 502 | LOCAL(void)static void | |||
| 503 | compute_color (j_decompress_ptr cinfo, boxptr boxp, int icolor) | |||
| 504 | /* Compute representative color for a box, put it in colormap[icolor] */ | |||
| 505 | { | |||
| 506 | /* Current algorithm: mean weighted by pixels (not colors) */ | |||
| 507 | /* Note it is important to get the rounding correct! */ | |||
| 508 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 509 | hist3d histogram = cquantize->histogram; | |||
| 510 | histptr histp; | |||
| 511 | int c0,c1,c2; | |||
| 512 | int c0min,c0max,c1min,c1max,c2min,c2max; | |||
| 513 | long count; | |||
| 514 | long total = 0; | |||
| 515 | long c0total = 0; | |||
| 516 | long c1total = 0; | |||
| 517 | long c2total = 0; | |||
| 518 | ||||
| 519 | c0min = boxp->c0min; c0max = boxp->c0max; | |||
| 520 | c1min = boxp->c1min; c1max = boxp->c1max; | |||
| 521 | c2min = boxp->c2min; c2max = boxp->c2max; | |||
| 522 | ||||
| 523 | for (c0 = c0min; c0 <= c0max; c0++) | |||
| 524 | for (c1 = c1min; c1 <= c1max; c1++) { | |||
| 525 | histp = & histogram[c0][c1][c2min]; | |||
| 526 | for (c2 = c2min; c2 <= c2max; c2++) { | |||
| 527 | if ((count = *histp++) != 0) { | |||
| 528 | total += count; | |||
| 529 | c0total += ((c0 << C0_SHIFT(8 -5)) + ((1<<C0_SHIFT(8 -5))>>1)) * count; | |||
| 530 | c1total += ((c1 << C1_SHIFT(8 -6)) + ((1<<C1_SHIFT(8 -6))>>1)) * count; | |||
| 531 | c2total += ((c2 << C2_SHIFT(8 -5)) + ((1<<C2_SHIFT(8 -5))>>1)) * count; | |||
| 532 | } | |||
| 533 | } | |||
| 534 | } | |||
| 535 | ||||
| 536 | cinfo->colormap[0][icolor] = (JSAMPLE) ((c0total + (total>>1)) / total); | |||
| ||||
| 537 | cinfo->colormap[1][icolor] = (JSAMPLE) ((c1total + (total>>1)) / total); | |||
| 538 | cinfo->colormap[2][icolor] = (JSAMPLE) ((c2total + (total>>1)) / total); | |||
| 539 | } | |||
| 540 | ||||
| 541 | ||||
| 542 | LOCAL(void)static void | |||
| 543 | select_colors (j_decompress_ptr cinfo, int desired_colors) | |||
| 544 | /* Master routine for color selection */ | |||
| 545 | { | |||
| 546 | boxptr boxlist; | |||
| 547 | int numboxes; | |||
| 548 | int i; | |||
| 549 | ||||
| 550 | /* Allocate workspace for box list */ | |||
| 551 | boxlist = (boxptr) (*cinfo->mem->alloc_small) | |||
| 552 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, desired_colors * SIZEOF(box)((size_t) sizeof(box))); | |||
| 553 | /* Initialize one box containing whole space */ | |||
| 554 | numboxes = 1; | |||
| 555 | boxlist[0].c0min = 0; | |||
| 556 | boxlist[0].c0max = MAXJSAMPLE255 >> C0_SHIFT(8 -5); | |||
| 557 | boxlist[0].c1min = 0; | |||
| 558 | boxlist[0].c1max = MAXJSAMPLE255 >> C1_SHIFT(8 -6); | |||
| 559 | boxlist[0].c2min = 0; | |||
| 560 | boxlist[0].c2max = MAXJSAMPLE255 >> C2_SHIFT(8 -5); | |||
| 561 | /* Shrink it to actually-used volume and set its statistics */ | |||
| 562 | update_box(cinfo, & boxlist[0]); | |||
| 563 | /* Perform median-cut to produce final box list */ | |||
| 564 | numboxes = median_cut(cinfo, boxlist, numboxes, desired_colors); | |||
| 565 | /* Compute the representative color for each box, fill colormap */ | |||
| 566 | for (i = 0; i < numboxes; i++) | |||
| 567 | compute_color(cinfo, & boxlist[i], i); | |||
| 568 | cinfo->actual_number_of_colors = numboxes; | |||
| 569 | TRACEMS1(cinfo, 1, JTRC_QUANT_SELECTED, numboxes)((cinfo)->err->msg_code = (JTRC_QUANT_SELECTED), (cinfo )->err->msg_parm.i[0] = (numboxes), (*(cinfo)->err-> emit_message) ((j_common_ptr) (cinfo), (1))); | |||
| 570 | } | |||
| 571 | ||||
| 572 | ||||
| 573 | /* | |||
| 574 | * These routines are concerned with the time-critical task of mapping input | |||
| 575 | * colors to the nearest color in the selected colormap. | |||
| 576 | * | |||
| 577 | * We re-use the histogram space as an "inverse color map", essentially a | |||
| 578 | * cache for the results of nearest-color searches. All colors within a | |||
| 579 | * histogram cell will be mapped to the same colormap entry, namely the one | |||
| 580 | * closest to the cell's center. This may not be quite the closest entry to | |||
| 581 | * the actual input color, but it's almost as good. A zero in the cache | |||
| 582 | * indicates we haven't found the nearest color for that cell yet; the array | |||
| 583 | * is cleared to zeroes before starting the mapping pass. When we find the | |||
| 584 | * nearest color for a cell, its colormap index plus one is recorded in the | |||
| 585 | * cache for future use. The pass2 scanning routines call fill_inverse_cmap | |||
| 586 | * when they need to use an unfilled entry in the cache. | |||
| 587 | * | |||
| 588 | * Our method of efficiently finding nearest colors is based on the "locally | |||
| 589 | * sorted search" idea described by Heckbert and on the incremental distance | |||
| 590 | * calculation described by Spencer W. Thomas in chapter III.1 of Graphics | |||
| 591 | * Gems II (James Arvo, ed. Academic Press, 1991). Thomas points out that | |||
| 592 | * the distances from a given colormap entry to each cell of the histogram can | |||
| 593 | * be computed quickly using an incremental method: the differences between | |||
| 594 | * distances to adjacent cells themselves differ by a constant. This allows a | |||
| 595 | * fairly fast implementation of the "brute force" approach of computing the | |||
| 596 | * distance from every colormap entry to every histogram cell. Unfortunately, | |||
| 597 | * it needs a work array to hold the best-distance-so-far for each histogram | |||
| 598 | * cell (because the inner loop has to be over cells, not colormap entries). | |||
| 599 | * The work array elements have to be INT32s, so the work array would need | |||
| 600 | * 256Kb at our recommended precision. This is not feasible in DOS machines. | |||
| 601 | * | |||
| 602 | * To get around these problems, we apply Thomas' method to compute the | |||
| 603 | * nearest colors for only the cells within a small subbox of the histogram. | |||
| 604 | * The work array need be only as big as the subbox, so the memory usage | |||
| 605 | * problem is solved. Furthermore, we need not fill subboxes that are never | |||
| 606 | * referenced in pass2; many images use only part of the color gamut, so a | |||
| 607 | * fair amount of work is saved. An additional advantage of this | |||
| 608 | * approach is that we can apply Heckbert's locality criterion to quickly | |||
| 609 | * eliminate colormap entries that are far away from the subbox; typically | |||
| 610 | * three-fourths of the colormap entries are rejected by Heckbert's criterion, | |||
| 611 | * and we need not compute their distances to individual cells in the subbox. | |||
| 612 | * The speed of this approach is heavily influenced by the subbox size: too | |||
| 613 | * small means too much overhead, too big loses because Heckbert's criterion | |||
| 614 | * can't eliminate as many colormap entries. Empirically the best subbox | |||
| 615 | * size seems to be about 1/512th of the histogram (1/8th in each direction). | |||
| 616 | * | |||
| 617 | * Thomas' article also describes a refined method which is asymptotically | |||
| 618 | * faster than the brute-force method, but it is also far more complex and | |||
| 619 | * cannot efficiently be applied to small subboxes. It is therefore not | |||
| 620 | * useful for programs intended to be portable to DOS machines. On machines | |||
| 621 | * with plenty of memory, filling the whole histogram in one shot with Thomas' | |||
| 622 | * refined method might be faster than the present code --- but then again, | |||
| 623 | * it might not be any faster, and it's certainly more complicated. | |||
| 624 | */ | |||
| 625 | ||||
| 626 | ||||
| 627 | /* log2(histogram cells in update box) for each axis; this can be adjusted */ | |||
| 628 | #define BOX_C0_LOG(5 -3) (HIST_C0_BITS5-3) | |||
| 629 | #define BOX_C1_LOG(6 -3) (HIST_C1_BITS6-3) | |||
| 630 | #define BOX_C2_LOG(5 -3) (HIST_C2_BITS5-3) | |||
| 631 | ||||
| 632 | #define BOX_C0_ELEMS(1<<(5 -3)) (1<<BOX_C0_LOG(5 -3)) /* # of hist cells in update box */ | |||
| 633 | #define BOX_C1_ELEMS(1<<(6 -3)) (1<<BOX_C1_LOG(6 -3)) | |||
| 634 | #define BOX_C2_ELEMS(1<<(5 -3)) (1<<BOX_C2_LOG(5 -3)) | |||
| 635 | ||||
| 636 | #define BOX_C0_SHIFT((8 -5) + (5 -3)) (C0_SHIFT(8 -5) + BOX_C0_LOG(5 -3)) | |||
| 637 | #define BOX_C1_SHIFT((8 -6) + (6 -3)) (C1_SHIFT(8 -6) + BOX_C1_LOG(6 -3)) | |||
| 638 | #define BOX_C2_SHIFT((8 -5) + (5 -3)) (C2_SHIFT(8 -5) + BOX_C2_LOG(5 -3)) | |||
| 639 | ||||
| 640 | ||||
| 641 | /* | |||
| 642 | * The next three routines implement inverse colormap filling. They could | |||
| 643 | * all be folded into one big routine, but splitting them up this way saves | |||
| 644 | * some stack space (the mindist[] and bestdist[] arrays need not coexist) | |||
| 645 | * and may allow some compilers to produce better code by registerizing more | |||
| 646 | * inner-loop variables. | |||
| 647 | */ | |||
| 648 | ||||
| 649 | LOCAL(int)static int | |||
| 650 | find_nearby_colors (j_decompress_ptr cinfo, int minc0, int minc1, int minc2, | |||
| 651 | JSAMPLE colorlist[]) | |||
| 652 | /* Locate the colormap entries close enough to an update box to be candidates | |||
| 653 | * for the nearest entry to some cell(s) in the update box. The update box | |||
| 654 | * is specified by the center coordinates of its first cell. The number of | |||
| 655 | * candidate colormap entries is returned, and their colormap indexes are | |||
| 656 | * placed in colorlist[]. | |||
| 657 | * This routine uses Heckbert's "locally sorted search" criterion to select | |||
| 658 | * the colors that need further consideration. | |||
| 659 | */ | |||
| 660 | { | |||
| 661 | int numcolors = cinfo->actual_number_of_colors; | |||
| 662 | int maxc0, maxc1, maxc2; | |||
| 663 | int centerc0, centerc1, centerc2; | |||
| 664 | int i, x, ncolors; | |||
| 665 | INT32 minmaxdist, min_dist, max_dist, tdist; | |||
| 666 | INT32 mindist[MAXNUMCOLORS(255 +1)]; /* min distance to colormap entry i */ | |||
| 667 | ||||
| 668 | /* Compute true coordinates of update box's upper corner and center. | |||
| 669 | * Actually we compute the coordinates of the center of the upper-corner | |||
| 670 | * histogram cell, which are the upper bounds of the volume we care about. | |||
| 671 | * Note that since ">>" rounds down, the "center" values may be closer to | |||
| 672 | * min than to max; hence comparisons to them must be "<=", not "<". | |||
| 673 | */ | |||
| 674 | maxc0 = minc0 + ((1 << BOX_C0_SHIFT((8 -5) + (5 -3))) - (1 << C0_SHIFT(8 -5))); | |||
| 675 | centerc0 = (minc0 + maxc0) >> 1; | |||
| 676 | maxc1 = minc1 + ((1 << BOX_C1_SHIFT((8 -6) + (6 -3))) - (1 << C1_SHIFT(8 -6))); | |||
| 677 | centerc1 = (minc1 + maxc1) >> 1; | |||
| 678 | maxc2 = minc2 + ((1 << BOX_C2_SHIFT((8 -5) + (5 -3))) - (1 << C2_SHIFT(8 -5))); | |||
| 679 | centerc2 = (minc2 + maxc2) >> 1; | |||
| 680 | ||||
| 681 | /* For each color in colormap, find: | |||
| 682 | * 1. its minimum squared-distance to any point in the update box | |||
| 683 | * (zero if color is within update box); | |||
| 684 | * 2. its maximum squared-distance to any point in the update box. | |||
| 685 | * Both of these can be found by considering only the corners of the box. | |||
| 686 | * We save the minimum distance for each color in mindist[]; | |||
| 687 | * only the smallest maximum distance is of interest. | |||
| 688 | */ | |||
| 689 | minmaxdist = 0x7FFFFFFFL; | |||
| 690 | ||||
| 691 | for (i = 0; i < numcolors; i++) { | |||
| 692 | /* We compute the squared-c0-distance term, then add in the other two. */ | |||
| 693 | x = GETJSAMPLE(cinfo->colormap[0][i])((int) (cinfo->colormap[0][i])); | |||
| 694 | if (x < minc0) { | |||
| 695 | tdist = (x - minc0) * C0_SCALE2; | |||
| 696 | min_dist = tdist*tdist; | |||
| 697 | tdist = (x - maxc0) * C0_SCALE2; | |||
| 698 | max_dist = tdist*tdist; | |||
| 699 | } else if (x > maxc0) { | |||
| 700 | tdist = (x - maxc0) * C0_SCALE2; | |||
| 701 | min_dist = tdist*tdist; | |||
| 702 | tdist = (x - minc0) * C0_SCALE2; | |||
| 703 | max_dist = tdist*tdist; | |||
| 704 | } else { | |||
| 705 | /* within cell range so no contribution to min_dist */ | |||
| 706 | min_dist = 0; | |||
| 707 | if (x <= centerc0) { | |||
| 708 | tdist = (x - maxc0) * C0_SCALE2; | |||
| 709 | max_dist = tdist*tdist; | |||
| 710 | } else { | |||
| 711 | tdist = (x - minc0) * C0_SCALE2; | |||
| 712 | max_dist = tdist*tdist; | |||
| 713 | } | |||
| 714 | } | |||
| 715 | ||||
| 716 | x = GETJSAMPLE(cinfo->colormap[1][i])((int) (cinfo->colormap[1][i])); | |||
| 717 | if (x < minc1) { | |||
| 718 | tdist = (x - minc1) * C1_SCALE3; | |||
| 719 | min_dist += tdist*tdist; | |||
| 720 | tdist = (x - maxc1) * C1_SCALE3; | |||
| 721 | max_dist += tdist*tdist; | |||
| 722 | } else if (x > maxc1) { | |||
| 723 | tdist = (x - maxc1) * C1_SCALE3; | |||
| 724 | min_dist += tdist*tdist; | |||
| 725 | tdist = (x - minc1) * C1_SCALE3; | |||
| 726 | max_dist += tdist*tdist; | |||
| 727 | } else { | |||
| 728 | /* within cell range so no contribution to min_dist */ | |||
| 729 | if (x <= centerc1) { | |||
| 730 | tdist = (x - maxc1) * C1_SCALE3; | |||
| 731 | max_dist += tdist*tdist; | |||
| 732 | } else { | |||
| 733 | tdist = (x - minc1) * C1_SCALE3; | |||
| 734 | max_dist += tdist*tdist; | |||
| 735 | } | |||
| 736 | } | |||
| 737 | ||||
| 738 | x = GETJSAMPLE(cinfo->colormap[2][i])((int) (cinfo->colormap[2][i])); | |||
| 739 | if (x < minc2) { | |||
| 740 | tdist = (x - minc2) * C2_SCALE1; | |||
| 741 | min_dist += tdist*tdist; | |||
| 742 | tdist = (x - maxc2) * C2_SCALE1; | |||
| 743 | max_dist += tdist*tdist; | |||
| 744 | } else if (x > maxc2) { | |||
| 745 | tdist = (x - maxc2) * C2_SCALE1; | |||
| 746 | min_dist += tdist*tdist; | |||
| 747 | tdist = (x - minc2) * C2_SCALE1; | |||
| 748 | max_dist += tdist*tdist; | |||
| 749 | } else { | |||
| 750 | /* within cell range so no contribution to min_dist */ | |||
| 751 | if (x <= centerc2) { | |||
| 752 | tdist = (x - maxc2) * C2_SCALE1; | |||
| 753 | max_dist += tdist*tdist; | |||
| 754 | } else { | |||
| 755 | tdist = (x - minc2) * C2_SCALE1; | |||
| 756 | max_dist += tdist*tdist; | |||
| 757 | } | |||
| 758 | } | |||
| 759 | ||||
| 760 | mindist[i] = min_dist; /* save away the results */ | |||
| 761 | if (max_dist < minmaxdist) | |||
| 762 | minmaxdist = max_dist; | |||
| 763 | } | |||
| 764 | ||||
| 765 | /* Now we know that no cell in the update box is more than minmaxdist | |||
| 766 | * away from some colormap entry. Therefore, only colors that are | |||
| 767 | * within minmaxdist of some part of the box need be considered. | |||
| 768 | */ | |||
| 769 | ncolors = 0; | |||
| 770 | for (i = 0; i < numcolors; i++) { | |||
| 771 | if (mindist[i] <= minmaxdist) | |||
| 772 | colorlist[ncolors++] = (JSAMPLE) i; | |||
| 773 | } | |||
| 774 | return ncolors; | |||
| 775 | } | |||
| 776 | ||||
| 777 | ||||
| 778 | LOCAL(void)static void | |||
| 779 | find_best_colors (j_decompress_ptr cinfo, int minc0, int minc1, int minc2, | |||
| 780 | int numcolors, JSAMPLE colorlist[], JSAMPLE bestcolor[]) | |||
| 781 | /* Find the closest colormap entry for each cell in the update box, | |||
| 782 | * given the list of candidate colors prepared by find_nearby_colors. | |||
| 783 | * Return the indexes of the closest entries in the bestcolor[] array. | |||
| 784 | * This routine uses Thomas' incremental distance calculation method to | |||
| 785 | * find the distance from a colormap entry to successive cells in the box. | |||
| 786 | */ | |||
| 787 | { | |||
| 788 | int ic0, ic1, ic2; | |||
| 789 | int i, icolor; | |||
| 790 | register INT32 * bptr; /* pointer into bestdist[] array */ | |||
| 791 | JSAMPLE * cptr; /* pointer into bestcolor[] array */ | |||
| 792 | INT32 dist0, dist1; /* initial distance values */ | |||
| 793 | register INT32 dist2; /* current distance in inner loop */ | |||
| 794 | INT32 xx0, xx1; /* distance increments */ | |||
| 795 | register INT32 xx2; | |||
| 796 | INT32 inc0, inc1, inc2; /* initial values for increments */ | |||
| 797 | /* This array holds the distance to the nearest-so-far color for each cell */ | |||
| 798 | INT32 bestdist[BOX_C0_ELEMS(1<<(5 -3)) * BOX_C1_ELEMS(1<<(6 -3)) * BOX_C2_ELEMS(1<<(5 -3))]; | |||
| 799 | ||||
| 800 | /* Initialize best-distance for each cell of the update box */ | |||
| 801 | bptr = bestdist; | |||
| 802 | for (i = BOX_C0_ELEMS(1<<(5 -3))*BOX_C1_ELEMS(1<<(6 -3))*BOX_C2_ELEMS(1<<(5 -3))-1; i >= 0; i--) | |||
| 803 | *bptr++ = 0x7FFFFFFFL; | |||
| 804 | ||||
| 805 | /* For each color selected by find_nearby_colors, | |||
| 806 | * compute its distance to the center of each cell in the box. | |||
| 807 | * If that's less than best-so-far, update best distance and color number. | |||
| 808 | */ | |||
| 809 | ||||
| 810 | /* Nominal steps between cell centers ("x" in Thomas article) */ | |||
| 811 | #define STEP_C0((1 << (8 -5)) * 2) ((1 << C0_SHIFT(8 -5)) * C0_SCALE2) | |||
| 812 | #define STEP_C1((1 << (8 -6)) * 3) ((1 << C1_SHIFT(8 -6)) * C1_SCALE3) | |||
| 813 | #define STEP_C2((1 << (8 -5)) * 1) ((1 << C2_SHIFT(8 -5)) * C2_SCALE1) | |||
| 814 | ||||
| 815 | for (i = 0; i < numcolors; i++) { | |||
| 816 | icolor = GETJSAMPLE(colorlist[i])((int) (colorlist[i])); | |||
| 817 | /* Compute (square of) distance from minc0/c1/c2 to this color */ | |||
| 818 | inc0 = (minc0 - GETJSAMPLE(cinfo->colormap[0][icolor])((int) (cinfo->colormap[0][icolor]))) * C0_SCALE2; | |||
| 819 | dist0 = inc0*inc0; | |||
| 820 | inc1 = (minc1 - GETJSAMPLE(cinfo->colormap[1][icolor])((int) (cinfo->colormap[1][icolor]))) * C1_SCALE3; | |||
| 821 | dist0 += inc1*inc1; | |||
| 822 | inc2 = (minc2 - GETJSAMPLE(cinfo->colormap[2][icolor])((int) (cinfo->colormap[2][icolor]))) * C2_SCALE1; | |||
| 823 | dist0 += inc2*inc2; | |||
| 824 | /* Form the initial difference increments */ | |||
| 825 | inc0 = inc0 * (2 * STEP_C0((1 << (8 -5)) * 2)) + STEP_C0((1 << (8 -5)) * 2) * STEP_C0((1 << (8 -5)) * 2); | |||
| 826 | inc1 = inc1 * (2 * STEP_C1((1 << (8 -6)) * 3)) + STEP_C1((1 << (8 -6)) * 3) * STEP_C1((1 << (8 -6)) * 3); | |||
| 827 | inc2 = inc2 * (2 * STEP_C2((1 << (8 -5)) * 1)) + STEP_C2((1 << (8 -5)) * 1) * STEP_C2((1 << (8 -5)) * 1); | |||
| 828 | /* Now loop over all cells in box, updating distance per Thomas method */ | |||
| 829 | bptr = bestdist; | |||
| 830 | cptr = bestcolor; | |||
| 831 | xx0 = inc0; | |||
| 832 | for (ic0 = BOX_C0_ELEMS(1<<(5 -3))-1; ic0 >= 0; ic0--) { | |||
| 833 | dist1 = dist0; | |||
| 834 | xx1 = inc1; | |||
| 835 | for (ic1 = BOX_C1_ELEMS(1<<(6 -3))-1; ic1 >= 0; ic1--) { | |||
| 836 | dist2 = dist1; | |||
| 837 | xx2 = inc2; | |||
| 838 | for (ic2 = BOX_C2_ELEMS(1<<(5 -3))-1; ic2 >= 0; ic2--) { | |||
| 839 | if (dist2 < *bptr) { | |||
| 840 | *bptr = dist2; | |||
| 841 | *cptr = (JSAMPLE) icolor; | |||
| 842 | } | |||
| 843 | dist2 += xx2; | |||
| 844 | xx2 += 2 * STEP_C2((1 << (8 -5)) * 1) * STEP_C2((1 << (8 -5)) * 1); | |||
| 845 | bptr++; | |||
| 846 | cptr++; | |||
| 847 | } | |||
| 848 | dist1 += xx1; | |||
| 849 | xx1 += 2 * STEP_C1((1 << (8 -6)) * 3) * STEP_C1((1 << (8 -6)) * 3); | |||
| 850 | } | |||
| 851 | dist0 += xx0; | |||
| 852 | xx0 += 2 * STEP_C0((1 << (8 -5)) * 2) * STEP_C0((1 << (8 -5)) * 2); | |||
| 853 | } | |||
| 854 | } | |||
| 855 | } | |||
| 856 | ||||
| 857 | ||||
| 858 | LOCAL(void)static void | |||
| 859 | fill_inverse_cmap (j_decompress_ptr cinfo, int c0, int c1, int c2) | |||
| 860 | /* Fill the inverse-colormap entries in the update box that contains */ | |||
| 861 | /* histogram cell c0/c1/c2. (Only that one cell MUST be filled, but */ | |||
| 862 | /* we can fill as many others as we wish.) */ | |||
| 863 | { | |||
| 864 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 865 | hist3d histogram = cquantize->histogram; | |||
| 866 | int minc0, minc1, minc2; /* lower left corner of update box */ | |||
| 867 | int ic0, ic1, ic2; | |||
| 868 | register JSAMPLE * cptr; /* pointer into bestcolor[] array */ | |||
| 869 | register histptr cachep; /* pointer into main cache array */ | |||
| 870 | /* This array lists the candidate colormap indexes. */ | |||
| 871 | JSAMPLE colorlist[MAXNUMCOLORS(255 +1)]; | |||
| 872 | int numcolors; /* number of candidate colors */ | |||
| 873 | /* This array holds the actually closest colormap index for each cell. */ | |||
| 874 | JSAMPLE bestcolor[BOX_C0_ELEMS(1<<(5 -3)) * BOX_C1_ELEMS(1<<(6 -3)) * BOX_C2_ELEMS(1<<(5 -3))]; | |||
| 875 | ||||
| 876 | /* Convert cell coordinates to update box ID */ | |||
| 877 | c0 >>= BOX_C0_LOG(5 -3); | |||
| 878 | c1 >>= BOX_C1_LOG(6 -3); | |||
| 879 | c2 >>= BOX_C2_LOG(5 -3); | |||
| 880 | ||||
| 881 | /* Compute true coordinates of update box's origin corner. | |||
| 882 | * Actually we compute the coordinates of the center of the corner | |||
| 883 | * histogram cell, which are the lower bounds of the volume we care about. | |||
| 884 | */ | |||
| 885 | minc0 = (c0 << BOX_C0_SHIFT((8 -5) + (5 -3))) + ((1 << C0_SHIFT(8 -5)) >> 1); | |||
| 886 | minc1 = (c1 << BOX_C1_SHIFT((8 -6) + (6 -3))) + ((1 << C1_SHIFT(8 -6)) >> 1); | |||
| 887 | minc2 = (c2 << BOX_C2_SHIFT((8 -5) + (5 -3))) + ((1 << C2_SHIFT(8 -5)) >> 1); | |||
| 888 | ||||
| 889 | /* Determine which colormap entries are close enough to be candidates | |||
| 890 | * for the nearest entry to some cell in the update box. | |||
| 891 | */ | |||
| 892 | numcolors = find_nearby_colors(cinfo, minc0, minc1, minc2, colorlist); | |||
| 893 | ||||
| 894 | /* Determine the actually nearest colors. */ | |||
| 895 | find_best_colors(cinfo, minc0, minc1, minc2, numcolors, colorlist, | |||
| 896 | bestcolor); | |||
| 897 | ||||
| 898 | /* Save the best color numbers (plus 1) in the main cache array */ | |||
| 899 | c0 <<= BOX_C0_LOG(5 -3); /* convert ID back to base cell indexes */ | |||
| 900 | c1 <<= BOX_C1_LOG(6 -3); | |||
| 901 | c2 <<= BOX_C2_LOG(5 -3); | |||
| 902 | cptr = bestcolor; | |||
| 903 | for (ic0 = 0; ic0 < BOX_C0_ELEMS(1<<(5 -3)); ic0++) { | |||
| 904 | for (ic1 = 0; ic1 < BOX_C1_ELEMS(1<<(6 -3)); ic1++) { | |||
| 905 | cachep = & histogram[c0+ic0][c1+ic1][c2]; | |||
| 906 | for (ic2 = 0; ic2 < BOX_C2_ELEMS(1<<(5 -3)); ic2++) { | |||
| 907 | *cachep++ = (histcell) (GETJSAMPLE(*cptr++)((int) (*cptr++)) + 1); | |||
| 908 | } | |||
| 909 | } | |||
| 910 | } | |||
| 911 | } | |||
| 912 | ||||
| 913 | ||||
| 914 | /* | |||
| 915 | * Map some rows of pixels to the output colormapped representation. | |||
| 916 | */ | |||
| 917 | ||||
| 918 | METHODDEF(void)static void | |||
| 919 | pass2_no_dither (j_decompress_ptr cinfo, | |||
| 920 | JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows) | |||
| 921 | /* This version performs no dithering */ | |||
| 922 | { | |||
| 923 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 924 | hist3d histogram = cquantize->histogram; | |||
| 925 | register JSAMPROW inptr, outptr; | |||
| 926 | register histptr cachep; | |||
| 927 | register int c0, c1, c2; | |||
| 928 | int row; | |||
| 929 | JDIMENSION col; | |||
| 930 | JDIMENSION width = cinfo->output_width; | |||
| 931 | ||||
| 932 | for (row = 0; row < num_rows; row++) { | |||
| 933 | inptr = input_buf[row]; | |||
| 934 | outptr = output_buf[row]; | |||
| 935 | for (col = width; col > 0; col--) { | |||
| 936 | /* get pixel value and index into the cache */ | |||
| 937 | c0 = GETJSAMPLE(*inptr++)((int) (*inptr++)) >> C0_SHIFT(8 -5); | |||
| 938 | c1 = GETJSAMPLE(*inptr++)((int) (*inptr++)) >> C1_SHIFT(8 -6); | |||
| 939 | c2 = GETJSAMPLE(*inptr++)((int) (*inptr++)) >> C2_SHIFT(8 -5); | |||
| 940 | cachep = & histogram[c0][c1][c2]; | |||
| 941 | /* If we have not seen this color before, find nearest colormap entry */ | |||
| 942 | /* and update the cache */ | |||
| 943 | if (*cachep == 0) | |||
| 944 | fill_inverse_cmap(cinfo, c0,c1,c2); | |||
| 945 | /* Now emit the colormap index for this cell */ | |||
| 946 | *outptr++ = (JSAMPLE) (*cachep - 1); | |||
| 947 | } | |||
| 948 | } | |||
| 949 | } | |||
| 950 | ||||
| 951 | ||||
| 952 | METHODDEF(void)static void | |||
| 953 | pass2_fs_dither (j_decompress_ptr cinfo, | |||
| 954 | JSAMPARRAY input_buf, JSAMPARRAY output_buf, int num_rows) | |||
| 955 | /* This version performs Floyd-Steinberg dithering */ | |||
| 956 | { | |||
| 957 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 958 | hist3d histogram = cquantize->histogram; | |||
| 959 | register LOCFSERROR cur0, cur1, cur2; /* current error or pixel value */ | |||
| 960 | LOCFSERROR belowerr0, belowerr1, belowerr2; /* error for pixel below cur */ | |||
| 961 | LOCFSERROR bpreverr0, bpreverr1, bpreverr2; /* error for below/prev col */ | |||
| 962 | register FSERRPTR errorptr; /* => fserrors[] at column before current */ | |||
| 963 | JSAMPROW inptr; /* => current input pixel */ | |||
| 964 | JSAMPROW outptr; /* => current output pixel */ | |||
| 965 | histptr cachep; | |||
| 966 | int dir; /* +1 or -1 depending on direction */ | |||
| 967 | int dir3; /* 3*dir, for advancing inptr & errorptr */ | |||
| 968 | int row; | |||
| 969 | JDIMENSION col; | |||
| 970 | JDIMENSION width = cinfo->output_width; | |||
| 971 | JSAMPLE *range_limit = cinfo->sample_range_limit; | |||
| 972 | int *error_limit = cquantize->error_limiter; | |||
| 973 | JSAMPROW colormap0 = cinfo->colormap[0]; | |||
| 974 | JSAMPROW colormap1 = cinfo->colormap[1]; | |||
| 975 | JSAMPROW colormap2 = cinfo->colormap[2]; | |||
| 976 | SHIFT_TEMPS | |||
| 977 | ||||
| 978 | for (row = 0; row < num_rows; row++) { | |||
| 979 | inptr = input_buf[row]; | |||
| 980 | outptr = output_buf[row]; | |||
| 981 | if (cquantize->on_odd_row) { | |||
| 982 | /* work right to left in this row */ | |||
| 983 | inptr += (width-1) * 3; /* so point to rightmost pixel */ | |||
| 984 | outptr += width-1; | |||
| 985 | dir = -1; | |||
| 986 | dir3 = -3; | |||
| 987 | errorptr = cquantize->fserrors + (width+1)*3; /* => entry after last column */ | |||
| 988 | cquantize->on_odd_row = FALSE0; /* flip for next time */ | |||
| 989 | } else { | |||
| 990 | /* work left to right in this row */ | |||
| 991 | dir = 1; | |||
| 992 | dir3 = 3; | |||
| 993 | errorptr = cquantize->fserrors; /* => entry before first real column */ | |||
| 994 | cquantize->on_odd_row = TRUE1; /* flip for next time */ | |||
| 995 | } | |||
| 996 | /* Preset error values: no error propagated to first pixel from left */ | |||
| 997 | cur0 = cur1 = cur2 = 0; | |||
| 998 | /* and no error propagated to row below yet */ | |||
| 999 | belowerr0 = belowerr1 = belowerr2 = 0; | |||
| 1000 | bpreverr0 = bpreverr1 = bpreverr2 = 0; | |||
| 1001 | ||||
| 1002 | for (col = width; col > 0; col--) { | |||
| 1003 | /* curN holds the error propagated from the previous pixel on the | |||
| 1004 | * current line. Add the error propagated from the previous line | |||
| 1005 | * to form the complete error correction term for this pixel, and | |||
| 1006 | * round the error term (which is expressed * 16) to an integer. | |||
| 1007 | * RIGHT_SHIFT rounds towards minus infinity, so adding 8 is correct | |||
| 1008 | * for either sign of the error value. | |||
| 1009 | * Note: errorptr points to *previous* column's array entry. | |||
| 1010 | */ | |||
| 1011 | cur0 = RIGHT_SHIFT(cur0 + errorptr[dir3+0] + 8, 4)((cur0 + errorptr[dir3+0] + 8) >> (4)); | |||
| 1012 | cur1 = RIGHT_SHIFT(cur1 + errorptr[dir3+1] + 8, 4)((cur1 + errorptr[dir3+1] + 8) >> (4)); | |||
| 1013 | cur2 = RIGHT_SHIFT(cur2 + errorptr[dir3+2] + 8, 4)((cur2 + errorptr[dir3+2] + 8) >> (4)); | |||
| 1014 | /* Limit the error using transfer function set by init_error_limit. | |||
| 1015 | * See comments with init_error_limit for rationale. | |||
| 1016 | */ | |||
| 1017 | cur0 = error_limit[cur0]; | |||
| 1018 | cur1 = error_limit[cur1]; | |||
| 1019 | cur2 = error_limit[cur2]; | |||
| 1020 | /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE. | |||
| 1021 | * The maximum error is +- MAXJSAMPLE (or less with error limiting); | |||
| 1022 | * this sets the required size of the range_limit array. | |||
| 1023 | */ | |||
| 1024 | cur0 += GETJSAMPLE(inptr[0])((int) (inptr[0])); | |||
| 1025 | cur1 += GETJSAMPLE(inptr[1])((int) (inptr[1])); | |||
| 1026 | cur2 += GETJSAMPLE(inptr[2])((int) (inptr[2])); | |||
| 1027 | cur0 = GETJSAMPLE(range_limit[cur0])((int) (range_limit[cur0])); | |||
| 1028 | cur1 = GETJSAMPLE(range_limit[cur1])((int) (range_limit[cur1])); | |||
| 1029 | cur2 = GETJSAMPLE(range_limit[cur2])((int) (range_limit[cur2])); | |||
| 1030 | /* Index into the cache with adjusted pixel value */ | |||
| 1031 | cachep = & histogram[cur0>>C0_SHIFT(8 -5)][cur1>>C1_SHIFT(8 -6)][cur2>>C2_SHIFT(8 -5)]; | |||
| 1032 | /* If we have not seen this color before, find nearest colormap */ | |||
| 1033 | /* entry and update the cache */ | |||
| 1034 | if (*cachep == 0) | |||
| 1035 | fill_inverse_cmap(cinfo, cur0>>C0_SHIFT(8 -5),cur1>>C1_SHIFT(8 -6),cur2>>C2_SHIFT(8 -5)); | |||
| 1036 | /* Now emit the colormap index for this cell */ | |||
| 1037 | { register int pixcode = *cachep - 1; | |||
| 1038 | *outptr = (JSAMPLE) pixcode; | |||
| 1039 | /* Compute representation error for this pixel */ | |||
| 1040 | cur0 -= GETJSAMPLE(colormap0[pixcode])((int) (colormap0[pixcode])); | |||
| 1041 | cur1 -= GETJSAMPLE(colormap1[pixcode])((int) (colormap1[pixcode])); | |||
| 1042 | cur2 -= GETJSAMPLE(colormap2[pixcode])((int) (colormap2[pixcode])); | |||
| 1043 | } | |||
| 1044 | /* Compute error fractions to be propagated to adjacent pixels. | |||
| 1045 | * Add these into the running sums, and simultaneously shift the | |||
| 1046 | * next-line error sums left by 1 column. | |||
| 1047 | */ | |||
| 1048 | { register LOCFSERROR bnexterr, delta; | |||
| 1049 | ||||
| 1050 | bnexterr = cur0; /* Process component 0 */ | |||
| 1051 | delta = cur0 * 2; | |||
| 1052 | cur0 += delta; /* form error * 3 */ | |||
| 1053 | errorptr[0] = (FSERROR) (bpreverr0 + cur0); | |||
| 1054 | cur0 += delta; /* form error * 5 */ | |||
| 1055 | bpreverr0 = belowerr0 + cur0; | |||
| 1056 | belowerr0 = bnexterr; | |||
| 1057 | cur0 += delta; /* form error * 7 */ | |||
| 1058 | bnexterr = cur1; /* Process component 1 */ | |||
| 1059 | delta = cur1 * 2; | |||
| 1060 | cur1 += delta; /* form error * 3 */ | |||
| 1061 | errorptr[1] = (FSERROR) (bpreverr1 + cur1); | |||
| 1062 | cur1 += delta; /* form error * 5 */ | |||
| 1063 | bpreverr1 = belowerr1 + cur1; | |||
| 1064 | belowerr1 = bnexterr; | |||
| 1065 | cur1 += delta; /* form error * 7 */ | |||
| 1066 | bnexterr = cur2; /* Process component 2 */ | |||
| 1067 | delta = cur2 * 2; | |||
| 1068 | cur2 += delta; /* form error * 3 */ | |||
| 1069 | errorptr[2] = (FSERROR) (bpreverr2 + cur2); | |||
| 1070 | cur2 += delta; /* form error * 5 */ | |||
| 1071 | bpreverr2 = belowerr2 + cur2; | |||
| 1072 | belowerr2 = bnexterr; | |||
| 1073 | cur2 += delta; /* form error * 7 */ | |||
| 1074 | } | |||
| 1075 | /* At this point curN contains the 7/16 error value to be propagated | |||
| 1076 | * to the next pixel on the current line, and all the errors for the | |||
| 1077 | * next line have been shifted over. We are therefore ready to move on. | |||
| 1078 | */ | |||
| 1079 | inptr += dir3; /* Advance pixel pointers to next column */ | |||
| 1080 | outptr += dir; | |||
| 1081 | errorptr += dir3; /* advance errorptr to current column */ | |||
| 1082 | } | |||
| 1083 | /* Post-loop cleanup: we must unload the final error values into the | |||
| 1084 | * final fserrors[] entry. Note we need not unload belowerrN because | |||
| 1085 | * it is for the dummy column before or after the actual array. | |||
| 1086 | */ | |||
| 1087 | errorptr[0] = (FSERROR) bpreverr0; /* unload prev errs into array */ | |||
| 1088 | errorptr[1] = (FSERROR) bpreverr1; | |||
| 1089 | errorptr[2] = (FSERROR) bpreverr2; | |||
| 1090 | } | |||
| 1091 | } | |||
| 1092 | ||||
| 1093 | ||||
| 1094 | /* | |||
| 1095 | * Initialize the error-limiting transfer function (lookup table). | |||
| 1096 | * The raw F-S error computation can potentially compute error values of up to | |||
| 1097 | * +- MAXJSAMPLE. But we want the maximum correction applied to a pixel to be | |||
| 1098 | * much less, otherwise obviously wrong pixels will be created. (Typical | |||
| 1099 | * effects include weird fringes at color-area boundaries, isolated bright | |||
| 1100 | * pixels in a dark area, etc.) The standard advice for avoiding this problem | |||
| 1101 | * is to ensure that the "corners" of the color cube are allocated as output | |||
| 1102 | * colors; then repeated errors in the same direction cannot cause cascading | |||
| 1103 | * error buildup. However, that only prevents the error from getting | |||
| 1104 | * completely out of hand; Aaron Giles reports that error limiting improves | |||
| 1105 | * the results even with corner colors allocated. | |||
| 1106 | * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty | |||
| 1107 | * well, but the smoother transfer function used below is even better. Thanks | |||
| 1108 | * to Aaron Giles for this idea. | |||
| 1109 | */ | |||
| 1110 | ||||
| 1111 | LOCAL(void)static void | |||
| 1112 | init_error_limit (j_decompress_ptr cinfo) | |||
| 1113 | /* Allocate and fill in the error_limiter table */ | |||
| 1114 | { | |||
| 1115 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 1116 | int * table; | |||
| 1117 | int in, out; | |||
| 1118 | ||||
| 1119 | table = (int *) (*cinfo->mem->alloc_small) | |||
| 1120 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, (MAXJSAMPLE255*2+1) * SIZEOF(int)((size_t) sizeof(int))); | |||
| 1121 | table += MAXJSAMPLE255; /* so can index -MAXJSAMPLE .. +MAXJSAMPLE */ | |||
| 1122 | cquantize->error_limiter = table; | |||
| 1123 | ||||
| 1124 | #define STEPSIZE ((MAXJSAMPLE255+1)/16) | |||
| 1125 | /* Map errors 1:1 up to +- MAXJSAMPLE/16 */ | |||
| 1126 | out = 0; | |||
| 1127 | for (in = 0; in < STEPSIZE; in++, out++) { | |||
| 1128 | table[in] = out; table[-in] = -out; | |||
| 1129 | } | |||
| 1130 | /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */ | |||
| 1131 | for (; in < STEPSIZE*3; in++, out += (in&1) ? 0 : 1) { | |||
| 1132 | table[in] = out; table[-in] = -out; | |||
| 1133 | } | |||
| 1134 | /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */ | |||
| 1135 | for (; in <= MAXJSAMPLE255; in++) { | |||
| 1136 | table[in] = out; table[-in] = -out; | |||
| 1137 | } | |||
| 1138 | #undef STEPSIZE | |||
| 1139 | } | |||
| 1140 | ||||
| 1141 | ||||
| 1142 | /* | |||
| 1143 | * Finish up at the end of each pass. | |||
| 1144 | */ | |||
| 1145 | ||||
| 1146 | METHODDEF(void)static void | |||
| 1147 | finish_pass1 (j_decompress_ptr cinfo) | |||
| 1148 | { | |||
| 1149 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 1150 | ||||
| 1151 | /* Select the representative colors and fill in cinfo->colormap */ | |||
| 1152 | cinfo->colormap = cquantize->sv_colormap; | |||
| 1153 | select_colors(cinfo, cquantize->desired); | |||
| ||||
| 1154 | /* Force next pass to zero the color index table */ | |||
| 1155 | cquantize->needs_zeroed = TRUE1; | |||
| 1156 | } | |||
| 1157 | ||||
| 1158 | ||||
| 1159 | METHODDEF(void)static void | |||
| 1160 | finish_pass2 (j_decompress_ptr cinfo) | |||
| 1161 | { | |||
| 1162 | /* no work */ | |||
| 1163 | } | |||
| 1164 | ||||
| 1165 | ||||
| 1166 | /* | |||
| 1167 | * Initialize for each processing pass. | |||
| 1168 | */ | |||
| 1169 | ||||
| 1170 | METHODDEF(void)static void | |||
| 1171 | start_pass_2_quant (j_decompress_ptr cinfo, boolean is_pre_scan) | |||
| 1172 | { | |||
| 1173 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 1174 | hist3d histogram = cquantize->histogram; | |||
| 1175 | int i; | |||
| 1176 | ||||
| 1177 | /* Only F-S dithering or no dithering is supported. */ | |||
| 1178 | /* If user asks for ordered dither, give him F-S. */ | |||
| 1179 | if (cinfo->dither_mode != JDITHER_NONE) | |||
| 1180 | cinfo->dither_mode = JDITHER_FS; | |||
| 1181 | ||||
| 1182 | if (is_pre_scan) { | |||
| 1183 | /* Set up method pointers */ | |||
| 1184 | cquantize->pub.color_quantize = prescan_quantize; | |||
| 1185 | cquantize->pub.finish_pass = finish_pass1; | |||
| 1186 | cquantize->needs_zeroed = TRUE1; /* Always zero histogram */ | |||
| 1187 | } else { | |||
| 1188 | /* Set up method pointers */ | |||
| 1189 | if (cinfo->dither_mode == JDITHER_FS) | |||
| 1190 | cquantize->pub.color_quantize = pass2_fs_dither; | |||
| 1191 | else | |||
| 1192 | cquantize->pub.color_quantize = pass2_no_dither; | |||
| 1193 | cquantize->pub.finish_pass = finish_pass2; | |||
| 1194 | ||||
| 1195 | /* Make sure color count is acceptable */ | |||
| 1196 | i = cinfo->actual_number_of_colors; | |||
| 1197 | if (i < 1) | |||
| 1198 | ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 1)((cinfo)->err->msg_code = (JERR_QUANT_FEW_COLORS), (cinfo )->err->msg_parm.i[0] = (1), (*(cinfo)->err->error_exit ) ((j_common_ptr) (cinfo))); | |||
| 1199 | if (i > MAXNUMCOLORS(255 +1)) | |||
| 1200 | ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS)((cinfo)->err->msg_code = (JERR_QUANT_MANY_COLORS), (cinfo )->err->msg_parm.i[0] = ((255 +1)), (*(cinfo)->err-> error_exit) ((j_common_ptr) (cinfo))); | |||
| 1201 | ||||
| 1202 | if (cinfo->dither_mode == JDITHER_FS) { | |||
| 1203 | size_t arraysize = (size_t) ((cinfo->output_width + 2) * | |||
| 1204 | (3 * SIZEOF(FSERROR)((size_t) sizeof(FSERROR)))); | |||
| 1205 | /* Allocate Floyd-Steinberg workspace if we didn't already. */ | |||
| 1206 | if (cquantize->fserrors == NULL((void*)0)) | |||
| 1207 | cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large) | |||
| 1208 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, arraysize); | |||
| 1209 | /* Initialize the propagated errors to zero. */ | |||
| 1210 | jzero_farjZeroFar((void FAR *) cquantize->fserrors, arraysize); | |||
| 1211 | /* Make the error-limit table if we didn't already. */ | |||
| 1212 | if (cquantize->error_limiter == NULL((void*)0)) | |||
| 1213 | init_error_limit(cinfo); | |||
| 1214 | cquantize->on_odd_row = FALSE0; | |||
| 1215 | } | |||
| 1216 | ||||
| 1217 | } | |||
| 1218 | /* Zero the histogram or inverse color map, if necessary */ | |||
| 1219 | if (cquantize->needs_zeroed) { | |||
| 1220 | for (i = 0; i < HIST_C0_ELEMS(1<<5); i++) { | |||
| 1221 | jzero_farjZeroFar((void FAR *) histogram[i], | |||
| 1222 | HIST_C1_ELEMS(1<<6)*HIST_C2_ELEMS(1<<5) * SIZEOF(histcell)((size_t) sizeof(histcell))); | |||
| 1223 | } | |||
| 1224 | cquantize->needs_zeroed = FALSE0; | |||
| 1225 | } | |||
| 1226 | } | |||
| 1227 | ||||
| 1228 | ||||
| 1229 | /* | |||
| 1230 | * Switch to a new external colormap between output passes. | |||
| 1231 | */ | |||
| 1232 | ||||
| 1233 | METHODDEF(void)static void | |||
| 1234 | new_color_map_2_quant (j_decompress_ptr cinfo) | |||
| 1235 | { | |||
| 1236 | my_cquantize_ptr cquantize = (my_cquantize_ptr) cinfo->cquantize; | |||
| 1237 | ||||
| 1238 | /* Reset the inverse color map */ | |||
| 1239 | cquantize->needs_zeroed = TRUE1; | |||
| 1240 | } | |||
| 1241 | ||||
| 1242 | ||||
| 1243 | /* | |||
| 1244 | * Module initialization routine for 2-pass color quantization. | |||
| 1245 | */ | |||
| 1246 | ||||
| 1247 | GLOBAL(void)void | |||
| 1248 | jinit_2pass_quantizerjI2Quant (j_decompress_ptr cinfo) | |||
| 1249 | { | |||
| 1250 | my_cquantize_ptr cquantize; | |||
| 1251 | int i; | |||
| 1252 | ||||
| 1253 | cquantize = (my_cquantize_ptr) | |||
| 1254 | (*cinfo->mem->alloc_small) ((j_common_ptr) cinfo, JPOOL_IMAGE1, | |||
| 1255 | SIZEOF(my_cquantizer)((size_t) sizeof(my_cquantizer))); | |||
| 1256 | cinfo->cquantize = (struct jpeg_color_quantizer *) cquantize; | |||
| 1257 | cquantize->pub.start_pass = start_pass_2_quant; | |||
| 1258 | cquantize->pub.new_color_map = new_color_map_2_quant; | |||
| 1259 | cquantize->fserrors = NULL((void*)0); /* flag optional arrays not allocated */ | |||
| 1260 | cquantize->error_limiter = NULL((void*)0); | |||
| 1261 | ||||
| 1262 | /* Make sure jdmaster didn't give me a case I can't handle */ | |||
| 1263 | if (cinfo->out_color_components != 3) | |||
| 1264 | ERREXIT(cinfo, JERR_NOTIMPL)((cinfo)->err->msg_code = (JERR_NOTIMPL), (*(cinfo)-> err->error_exit) ((j_common_ptr) (cinfo))); | |||
| 1265 | ||||
| 1266 | /* Allocate the histogram/inverse colormap storage */ | |||
| 1267 | cquantize->histogram = (hist3d) (*cinfo->mem->alloc_small) | |||
| 1268 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, HIST_C0_ELEMS(1<<5) * SIZEOF(hist2d)((size_t) sizeof(hist2d))); | |||
| 1269 | for (i = 0; i < HIST_C0_ELEMS(1<<5); i++) { | |||
| 1270 | cquantize->histogram[i] = (hist2d) (*cinfo->mem->alloc_large) | |||
| 1271 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, | |||
| 1272 | HIST_C1_ELEMS(1<<6)*HIST_C2_ELEMS(1<<5) * SIZEOF(histcell)((size_t) sizeof(histcell))); | |||
| 1273 | } | |||
| 1274 | cquantize->needs_zeroed = TRUE1; /* histogram is garbage now */ | |||
| 1275 | ||||
| 1276 | /* Allocate storage for the completed colormap, if required. | |||
| 1277 | * We do this now since it is FAR storage and may affect | |||
| 1278 | * the memory manager's space calculations. | |||
| 1279 | */ | |||
| 1280 | if (cinfo->enable_2pass_quant) { | |||
| 1281 | /* Make sure color count is acceptable */ | |||
| 1282 | int desired = cinfo->desired_number_of_colors; | |||
| 1283 | /* Lower bound on # of colors ... somewhat arbitrary as long as > 0 */ | |||
| 1284 | if (desired < 8) | |||
| 1285 | ERREXIT1(cinfo, JERR_QUANT_FEW_COLORS, 8)((cinfo)->err->msg_code = (JERR_QUANT_FEW_COLORS), (cinfo )->err->msg_parm.i[0] = (8), (*(cinfo)->err->error_exit ) ((j_common_ptr) (cinfo))); | |||
| 1286 | /* Make sure colormap indexes can be represented by JSAMPLEs */ | |||
| 1287 | if (desired > MAXNUMCOLORS(255 +1)) | |||
| 1288 | ERREXIT1(cinfo, JERR_QUANT_MANY_COLORS, MAXNUMCOLORS)((cinfo)->err->msg_code = (JERR_QUANT_MANY_COLORS), (cinfo )->err->msg_parm.i[0] = ((255 +1)), (*(cinfo)->err-> error_exit) ((j_common_ptr) (cinfo))); | |||
| 1289 | cquantize->sv_colormap = (*cinfo->mem->alloc_sarray) | |||
| 1290 | ((j_common_ptr) cinfo,JPOOL_IMAGE1, (JDIMENSION) desired, (JDIMENSION) 3); | |||
| 1291 | cquantize->desired = desired; | |||
| 1292 | } else | |||
| 1293 | cquantize->sv_colormap = NULL((void*)0); | |||
| 1294 | ||||
| 1295 | /* Only F-S dithering or no dithering is supported. */ | |||
| 1296 | /* If user asks for ordered dither, give him F-S. */ | |||
| 1297 | if (cinfo->dither_mode != JDITHER_NONE) | |||
| 1298 | cinfo->dither_mode = JDITHER_FS; | |||
| 1299 | ||||
| 1300 | /* Allocate Floyd-Steinberg workspace if necessary. | |||
| 1301 | * This isn't really needed until pass 2, but again it is FAR storage. | |||
| 1302 | * Although we will cope with a later change in dither_mode, | |||
| 1303 | * we do not promise to honor max_memory_to_use if dither_mode changes. | |||
| 1304 | */ | |||
| 1305 | if (cinfo->dither_mode == JDITHER_FS) { | |||
| 1306 | cquantize->fserrors = (FSERRPTR) (*cinfo->mem->alloc_large) | |||
| 1307 | ((j_common_ptr) cinfo, JPOOL_IMAGE1, | |||
| 1308 | (size_t) ((cinfo->output_width + 2) * (3 * SIZEOF(FSERROR)((size_t) sizeof(FSERROR))))); | |||
| 1309 | /* Might as well create the error-limiting table too. */ | |||
| 1310 | init_error_limit(cinfo); | |||
| 1311 | } | |||
| 1312 | } | |||
| 1313 | ||||
| 1314 | #endif /* QUANT_2PASS_SUPPORTED */ |