1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167
|
/*
* UFRaw - Unidentified Flying Raw converter for digital camera images
*
* dcraw_indi.c - DCRaw functions made independent
* Copyright 2004-2014 by Udi Fuchs
*
* based on dcraw by Dave Coffin
* http://www.cybercom.net/~dcoffin/
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*/
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#include <glib.h>
#include <glib/gi18n.h> /*For _(String) definition - NKBJ*/
#include "dcraw_api.h"
#include "uf_progress.h"
#ifdef _OPENMP
#include <omp.h>
#define uf_omp_get_thread_num() omp_get_thread_num()
#define uf_omp_get_num_threads() omp_get_num_threads()
#else
#define uf_omp_get_thread_num() 0
#define uf_omp_get_num_threads() 1
#endif
#if !defined(ushort)
#define ushort unsigned short
#endif
extern const double xyz_rgb[3][3];
extern const float d65_white[3];
#define CLASS
#define FORC(cnt) for (c=0; c < cnt; c++)
#define FORC3 FORC(3)
#define FORC4 FORC(4)
#define FORCC FORC(colors)
#define SQR(x) ((x)*(x))
#define LIM(x,min,max) MAX(min,MIN(x,max))
#define ULIM(x,y,z) ((y) < (z) ? LIM(x,y,z) : LIM(x,z,y))
#define CLIP(x) LIM(x,0,65535)
#define SWAP(a,b) { a ^= b; a ^= (b ^= a); }
/*
In order to inline this calculation, I make the risky
assumption that all filter patterns can be described
by a repeating pattern of eight rows and two columns
Return values are either 0/1/2/3 = G/M/C/Y or 0/1/2/3 = R/G1/B/G2
*/
#define FC(row,col) \
(int)(filters >> ((((row) << 1 & 14) + ((col) & 1)) << 1) & 3)
#define BAYER(row,col) \
image[((row) >> shrink)*iwidth + ((col) >> shrink)][FC(row,col)]
int CLASS fcol_INDI(const unsigned filters, const int row, const int col,
const int top_margin, const int left_margin,
/*const*/ char xtrans[6][6])
{
static const char filter[16][16] = {
{ 2, 1, 1, 3, 2, 3, 2, 0, 3, 2, 3, 0, 1, 2, 1, 0 },
{ 0, 3, 0, 2, 0, 1, 3, 1, 0, 1, 1, 2, 0, 3, 3, 2 },
{ 2, 3, 3, 2, 3, 1, 1, 3, 3, 1, 2, 1, 2, 0, 0, 3 },
{ 0, 1, 0, 1, 0, 2, 0, 2, 2, 0, 3, 0, 1, 3, 2, 1 },
{ 3, 1, 1, 2, 0, 1, 0, 2, 1, 3, 1, 3, 0, 1, 3, 0 },
{ 2, 0, 0, 3, 3, 2, 3, 1, 2, 0, 2, 0, 3, 2, 2, 1 },
{ 2, 3, 3, 1, 2, 1, 2, 1, 2, 1, 1, 2, 3, 0, 0, 1 },
{ 1, 0, 0, 2, 3, 0, 0, 3, 0, 3, 0, 3, 2, 1, 2, 3 },
{ 2, 3, 3, 1, 1, 2, 1, 0, 3, 2, 3, 0, 2, 3, 1, 3 },
{ 1, 0, 2, 0, 3, 0, 3, 2, 0, 1, 1, 2, 0, 1, 0, 2 },
{ 0, 1, 1, 3, 3, 2, 2, 1, 1, 3, 3, 0, 2, 1, 3, 2 },
{ 2, 3, 2, 0, 0, 1, 3, 0, 2, 0, 1, 2, 3, 0, 1, 0 },
{ 1, 3, 1, 2, 3, 2, 3, 2, 0, 2, 0, 1, 1, 0, 3, 0 },
{ 0, 2, 0, 3, 1, 0, 0, 1, 1, 3, 3, 2, 3, 2, 2, 1 },
{ 2, 1, 3, 2, 3, 1, 2, 1, 0, 3, 0, 2, 0, 2, 0, 2 },
{ 0, 3, 1, 0, 0, 2, 0, 3, 2, 1, 3, 1, 1, 3, 1, 3 }
};
if (filters == 1) return filter[(row + top_margin) & 15][(col + left_margin) & 15];
if (filters == 9) return xtrans[(row + 6) % 6][(col + 6) % 6];
return FC(row, col);
}
static void CLASS merror(void *ptr, char *where)
{
if (ptr) return;
g_error("Out of memory in %s\n", where);
}
static void CLASS hat_transform(float *temp, float *base, int st, int size, int sc)
{
int i;
for (i = 0; i < sc; i++)
temp[i] = 2 * base[st * i] + base[st * (sc - i)] + base[st * (i + sc)];
for (; i + sc < size; i++)
temp[i] = 2 * base[st * i] + base[st * (i - sc)] + base[st * (i + sc)];
for (; i < size; i++)
temp[i] = 2 * base[st * i] + base[st * (i - sc)] + base[st * (2 * size - 2 - (i + sc))];
}
void CLASS wavelet_denoise_INDI(ushort(*image)[4], const int black,
const int iheight, const int iwidth,
const int height, const int width,
const int colors, const int shrink,
const float pre_mul[4], const float threshold,
const unsigned filters)
{
float *fimg = 0, thold, mul[2], avg, diff;
int size, lev, hpass, lpass, row, col, nc, c, i, wlast;
ushort *window[4];
static const float noise[] =
{ 0.8002, 0.2735, 0.1202, 0.0585, 0.0291, 0.0152, 0.0080, 0.0044 };
// dcraw_message (dcraw, DCRAW_VERBOSE,_("Wavelet denoising...\n")); /*UF*/
/* Scaling is done somewhere else - NKBJ*/
size = iheight * iwidth;
float temp[iheight + iwidth];
if ((nc = colors) == 3 && filters) nc++;
progress(PROGRESS_WAVELET_DENOISE, -nc * 5);
#ifdef _OPENMP
#if defined(__sun) && !defined(__GNUC__) /* Fix bug #3205673 - NKBJ */
#pragma omp parallel for \
default(none) \
shared(nc,image,size,noise) \
private(c,i,hpass,lev,lpass,row,col,thold,fimg,temp)
#else
#pragma omp parallel for \
default(none) \
shared(nc,image,size) \
private(c,i,hpass,lev,lpass,row,col,thold,fimg,temp)
#endif
#endif
FORC(nc) { /* denoise R,G1,B,G3 individually */
fimg = (float *) malloc(size * 3 * sizeof * fimg);
for (i = 0; i < size; i++)
fimg[i] = 256 * sqrt(image[i][c] /*<< scale*/);
for (hpass = lev = 0; lev < 5; lev++) {
progress(PROGRESS_WAVELET_DENOISE, 1);
lpass = size * ((lev & 1) + 1);
for (row = 0; row < iheight; row++) {
hat_transform(temp, fimg + hpass + row * iwidth, 1, iwidth, 1 << lev);
for (col = 0; col < iwidth; col++)
fimg[lpass + row * iwidth + col] = temp[col] * 0.25;
}
for (col = 0; col < iwidth; col++) {
hat_transform(temp, fimg + lpass + col, iwidth, iheight, 1 << lev);
for (row = 0; row < iheight; row++)
fimg[lpass + row * iwidth + col] = temp[row] * 0.25;
}
thold = threshold * noise[lev];
for (i = 0; i < size; i++) {
fimg[hpass + i] -= fimg[lpass + i];
if (fimg[hpass + i] < -thold) fimg[hpass + i] += thold;
else if (fimg[hpass + i] > thold) fimg[hpass + i] -= thold;
else fimg[hpass + i] = 0;
if (hpass) fimg[i] += fimg[hpass + i];
}
hpass = lpass;
}
for (i = 0; i < size; i++)
image[i][c] = CLIP(SQR(fimg[i] + fimg[lpass + i]) / 0x10000);
free(fimg);
}
if (filters && colors == 3) { /* pull G1 and G3 closer together */
for (row = 0; row < 2; row++)
mul[row] = 0.125 * pre_mul[FC(row + 1, 0) | 1] / pre_mul[FC(row, 0) | 1];
ushort window_mem[4][width];
for (i = 0; i < 4; i++)
window[i] = window_mem[i]; /*(ushort *) fimg + width*i;*/
for (wlast = -1, row = 1; row < height - 1; row++) {
while (wlast < row + 1) {
for (wlast++, i = 0; i < 4; i++)
window[(i + 3) & 3] = window[i];
for (col = FC(wlast, 1) & 1; col < width; col += 2)
window[2][col] = BAYER(wlast, col);
}
thold = threshold / 512;
for (col = (FC(row, 0) & 1) + 1; col < width - 1; col += 2) {
avg = (window[0][col - 1] + window[0][col + 1] +
window[2][col - 1] + window[2][col + 1] - black * 4)
* mul[row & 1] + (window[1][col] - black) * 0.5 + black;
avg = avg < 0 ? 0 : sqrt(avg);
diff = sqrt(BAYER(row, col)) - avg;
if (diff < -thold) diff += thold;
else if (diff > thold) diff -= thold;
else diff = 0;
BAYER(row, col) = CLIP(SQR(avg + diff) + 0.5);
}
}
}
}
void CLASS scale_colors_INDI(const int maximum, const int black,
const int use_camera_wb, const float cam_mul[4], const int colors,
float pre_mul[4], const unsigned filters, /*const*/ ushort white[8][8],
const char *ifname_display, void *dcraw)
{
unsigned row, col, c, sum[8];
int val;
double dmin, dmax;
if (use_camera_wb && cam_mul[0] != -1) {
memset(sum, 0, sizeof sum);
for (row = 0; row < 8; row++)
for (col = 0; col < 8; col++) {
c = FC(row, col);
if ((val = white[row][col] - black) > 0)
sum[c] += val;
sum[c + 4]++;
}
if (sum[0] && sum[1] && sum[2] && sum[3])
FORC4 pre_mul[c] = (float) sum[c + 4] / sum[c];
else if (cam_mul[0] && cam_mul[2])
/* 'sizeof pre_mul' does not work because pre_mul is an argument (UF)*/
memcpy(pre_mul, cam_mul, 4 * sizeof(float));
else
dcraw_message(dcraw, DCRAW_NO_CAMERA_WB,
_("%s: Cannot use camera white balance.\n"), ifname_display);
} else {
dcraw_message(dcraw, DCRAW_NO_CAMERA_WB,
_("%s: Cannot use camera white balance.\n"), ifname_display);
}
if (pre_mul[1] == 0) pre_mul[1] = 1;
if (pre_mul[3] == 0) pre_mul[3] = colors < 4 ? pre_mul[1] : 1;
for (dmin = DBL_MAX, dmax = c = 0; c < 4; c++) {
if (dmin > pre_mul[c])
dmin = pre_mul[c];
if (dmax < pre_mul[c])
dmax = pre_mul[c];
}
FORC4 pre_mul[c] /= dmax;
dcraw_message(dcraw, DCRAW_VERBOSE,
_("Scaling with darkness %d, saturation %d, and\nmultipliers"),
black, maximum);
FORC4 dcraw_message(dcraw, DCRAW_VERBOSE, " %f", pre_mul[c]);
dcraw_message(dcraw, DCRAW_VERBOSE, "\n");
/* The rest of the scaling is done somewhere else UF*/
}
void CLASS border_interpolate_INDI(const int height, const int width,
ushort(*image)[4], const unsigned filters, int colors, int border, dcraw_data *h)
{
int row, col, y, x, f, c, sum[8];
for (row = 0; row < height; row++)
for (col = 0; col < width; col++) {
if (col == border && row >= border && row < height - border)
col = width - border;
memset(sum, 0, sizeof sum);
for (y = row - 1; y != row + 2; y++)
for (x = col - 1; x != col + 2; x++)
if (y >= 0 && y < height && x >= 0 && x < width) {
f = fcol_INDI(filters, y, x, h->top_margin, h->left_margin, h->xtrans);
sum[f] += image[y * width + x][f];
sum[f + 4]++;
}
f = fcol_INDI(filters, row, col, h->top_margin, h->left_margin, h->xtrans);
FORCC if (c != f && sum[c + 4])
image[row * width + col][c] = sum[c] / sum[c + 4];
}
}
void CLASS lin_interpolate_INDI(ushort(*image)[4], const unsigned filters,
const int width, const int height, const int colors, void *dcraw, dcraw_data *h) /*UF*/
{
int code[16][16][32], size = 16, *ip, sum[4];
int f, c, i, x, y, row, col, shift, color;
ushort *pix;
dcraw_message(dcraw, DCRAW_VERBOSE, _("Bilinear interpolation...\n")); /*UF*/
if (filters == 9) size = 6;
border_interpolate_INDI(height, width, image, filters, colors, 1, h);
for (row = 0; row < size; row++) {
for (col = 0; col < size; col++) {
ip = code[row][col] + 1;
f = fcol_INDI(filters, row, col, h->top_margin, h->left_margin, h->xtrans);
memset(sum, 0, sizeof sum);
for (y = -1; y <= 1; y++)
for (x = -1; x <= 1; x++) {
shift = (y == 0) + (x == 0);
color = fcol_INDI(filters, row + y, col + x, h->top_margin, h->left_margin, h->xtrans);
if (color == f) continue;
*ip++ = (width * y + x) * 4 + color;
*ip++ = shift;
*ip++ = color;
sum[color] += 1 << shift;
}
code[row][col][0] = (ip - code[row][col]) / 3;
FORCC
if (c != f) {
*ip++ = c;
*ip++ = 256 / sum[c];
}
}
}
#ifdef _OPENMP
#pragma omp parallel for default(shared) private(row,col,pix,ip,sum,i)
#endif
for (row = 1; row < height - 1; row++) {
for (col = 1; col < width - 1; col++) {
pix = image[row * width + col];
ip = code[row % size][col % size];
memset(sum, 0, sizeof sum);
for (i = *ip++; i--; ip += 3)
sum[ip[2]] += pix[ip[0]] << ip[1];
for (i = colors; --i; ip += 2)
pix[ip[0]] = sum[ip[0]] * ip[1] >> 8;
}
}
}
/*
This algorithm is officially called:
"Interpolation using a Threshold-based variable number of gradients"
described in http://scien.stanford.edu/class/psych221/projects/99/tingchen/algodep/vargra.html
I've extended the basic idea to work with non-Bayer filter arrays.
Gradients are numbered clockwise from NW=0 to W=7.
*/
void CLASS vng_interpolate_INDI(ushort(*image)[4], const unsigned filters,
const int width, const int height, const int colors, void *dcraw, dcraw_data *h) /*UF*/
{
static const signed char *cp, terms[] = {
-2, -2, +0, -1, 0, 0x01, -2, -2, +0, +0, 1, 0x01, -2, -1, -1, +0, 0, 0x01,
-2, -1, +0, -1, 0, 0x02, -2, -1, +0, +0, 0, 0x03, -2, -1, +0, +1, 1, 0x01,
-2, +0, +0, -1, 0, 0x06, -2, +0, +0, +0, 1, 0x02, -2, +0, +0, +1, 0, 0x03,
-2, +1, -1, +0, 0, 0x04, -2, +1, +0, -1, 1, 0x04, -2, +1, +0, +0, 0, 0x06,
-2, +1, +0, +1, 0, 0x02, -2, +2, +0, +0, 1, 0x04, -2, +2, +0, +1, 0, 0x04,
-1, -2, -1, +0, 0, 0x80, -1, -2, +0, -1, 0, 0x01, -1, -2, +1, -1, 0, 0x01,
-1, -2, +1, +0, 1, 0x01, -1, -1, -1, +1, 0, 0x88, -1, -1, +1, -2, 0, 0x40,
-1, -1, +1, -1, 0, 0x22, -1, -1, +1, +0, 0, 0x33, -1, -1, +1, +1, 1, 0x11,
-1, +0, -1, +2, 0, 0x08, -1, +0, +0, -1, 0, 0x44, -1, +0, +0, +1, 0, 0x11,
-1, +0, +1, -2, 1, 0x40, -1, +0, +1, -1, 0, 0x66, -1, +0, +1, +0, 1, 0x22,
-1, +0, +1, +1, 0, 0x33, -1, +0, +1, +2, 1, 0x10, -1, +1, +1, -1, 1, 0x44,
-1, +1, +1, +0, 0, 0x66, -1, +1, +1, +1, 0, 0x22, -1, +1, +1, +2, 0, 0x10,
-1, +2, +0, +1, 0, 0x04, -1, +2, +1, +0, 1, 0x04, -1, +2, +1, +1, 0, 0x04,
+0, -2, +0, +0, 1, 0x80, +0, -1, +0, +1, 1, 0x88, +0, -1, +1, -2, 0, 0x40,
+0, -1, +1, +0, 0, 0x11, +0, -1, +2, -2, 0, 0x40, +0, -1, +2, -1, 0, 0x20,
+0, -1, +2, +0, 0, 0x30, +0, -1, +2, +1, 1, 0x10, +0, +0, +0, +2, 1, 0x08,
+0, +0, +2, -2, 1, 0x40, +0, +0, +2, -1, 0, 0x60, +0, +0, +2, +0, 1, 0x20,
+0, +0, +2, +1, 0, 0x30, +0, +0, +2, +2, 1, 0x10, +0, +1, +1, +0, 0, 0x44,
+0, +1, +1, +2, 0, 0x10, +0, +1, +2, -1, 1, 0x40, +0, +1, +2, +0, 0, 0x60,
+0, +1, +2, +1, 0, 0x20, +0, +1, +2, +2, 0, 0x10, +1, -2, +1, +0, 0, 0x80,
+1, -1, +1, +1, 0, 0x88, +1, +0, +1, +2, 0, 0x08, +1, +0, +2, -1, 0, 0x40,
+1, +0, +2, +1, 0, 0x10
}, chood[] = { -1, -1, -1, 0, -1, +1, 0, +1, +1, +1, +1, 0, +1, -1, 0, -1 };
ushort(*brow[4])[4], *pix;
int prow = 8, pcol = 2, *ip, *code[16][16], gval[8], gmin, gmax, sum[4];
int row, col, x, y, x1, x2, y1, y2, t, weight, grads, color, diag;
int g, diff, thold, num, c;
ushort rowtmp[4][width * 4];
lin_interpolate_INDI(image, filters, width, height, colors, dcraw, h); /*UF*/
dcraw_message(dcraw, DCRAW_VERBOSE, _("VNG interpolation...\n")); /*UF*/
if (filters == 1) prow = pcol = 16;
if (filters == 9) prow = pcol = 6;
int *ipalloc = ip = (int *) calloc(prow * pcol, 1280);
merror(ip, "vng_interpolate()");
for (row = 0; row < prow; row++) /* Precalculate for VNG */
for (col = 0; col < pcol; col++) {
code[row][col] = ip;
for (cp = terms, t = 0; t < 64; t++) {
y1 = *cp++;
x1 = *cp++;
y2 = *cp++;
x2 = *cp++;
weight = *cp++;
grads = *cp++;
color = fcol_INDI(filters, row + y1, col + x1, h->top_margin, h->left_margin, h->xtrans);
if (fcol_INDI(filters, row + y2, col + x2, h->top_margin, h->left_margin, h->xtrans) != color) continue;
diag = (fcol_INDI(filters, row, col + 1, h->top_margin, h->left_margin, h->xtrans) == color && fcol_INDI(filters, row + 1, col, h->top_margin, h->left_margin, h->xtrans) == color) ? 2 : 1;
if (abs(y1 - y2) == diag && abs(x1 - x2) == diag) continue;
*ip++ = (y1 * width + x1) * 4 + color;
*ip++ = (y2 * width + x2) * 4 + color;
*ip++ = weight;
for (g = 0; g < 8; g++)
if (grads & 1 << g) *ip++ = g;
*ip++ = -1;
}
*ip++ = INT_MAX;
for (cp = chood, g = 0; g < 8; g++) {
y = *cp++;
x = *cp++;
*ip++ = (y * width + x) * 4;
color = fcol_INDI(filters, row, col, h->top_margin, h->left_margin, h->xtrans);
if (fcol_INDI(filters, row + y, col + x, h->top_margin, h->left_margin, h->xtrans) != color && fcol_INDI(filters, row + y * 2, col + x * 2, h->top_margin, h->left_margin, h->xtrans) == color)
*ip++ = (y * width + x) * 8 + color;
else
*ip++ = 0;
}
}
progress(PROGRESS_INTERPOLATE, -height);
#ifdef _OPENMP
#pragma omp parallel \
default(none) \
shared(image,code,prow,pcol,h) \
private(row,col,g,brow,rowtmp,pix,ip,gval,diff,gmin,gmax,thold,sum,color,num,c,t)
#endif
{
int slice = (height - 4) / uf_omp_get_num_threads();
int start_row = 2 + slice * uf_omp_get_thread_num();
int end_row = MIN(start_row + slice, height - 2);
for (row = start_row; row < end_row; row++) { /* Do VNG interpolation */
progress(PROGRESS_INTERPOLATE, 1);
for (g = 0; g < 4; g++)
brow[g] = &rowtmp[(row + g - 2) % 4];
for (col = 2; col < width - 2; col++) {
pix = image[row * width + col];
ip = code[row % prow][col % pcol];
memset(gval, 0, sizeof gval);
while ((g = ip[0]) != INT_MAX) { /* Calculate gradients */
diff = ABS(pix[g] - pix[ip[1]]) << ip[2];
gval[ip[3]] += diff;
ip += 5;
if ((g = ip[-1]) == -1) continue;
gval[g] += diff;
while ((g = *ip++) != -1)
gval[g] += diff;
}
ip++;
gmin = gmax = gval[0]; /* Choose a threshold */
for (g = 1; g < 8; g++) {
if (gmin > gval[g]) gmin = gval[g];
if (gmax < gval[g]) gmax = gval[g];
}
if (gmax == 0) {
memcpy(brow[2][col], pix, sizeof * image);
continue;
}
thold = gmin + (gmax >> 1);
memset(sum, 0, sizeof sum);
color = fcol_INDI(filters, row, col, h->top_margin, h->left_margin, h->xtrans);
for (num = g = 0; g < 8; g++, ip += 2) { /* Average the neighbors */
if (gval[g] <= thold) {
FORCC
if (c == color && ip[1])
sum[c] += (pix[c] + pix[ip[1]]) >> 1;
else
sum[c] += pix[ip[0] + c];
num++;
}
}
FORCC { /* Save to buffer */
t = pix[color];
if (c != color)
t += (sum[c] - sum[color]) / num;
brow[2][col][c] = CLIP(t);
}
}
/* Write buffer to image */
if ((row > start_row + 1) || (row == height - 2))
memcpy(image[(row - 2)*width + 2], brow[0] + 2, (width - 4)*sizeof * image);
if (row == height - 2) {
memcpy(image[(row - 1)*width + 2], brow[1] + 2, (width - 4)*sizeof * image);
break;
}
}
}
free(ipalloc);
}
/*
Patterned Pixel Grouping Interpolation by Alain Desbiolles
*/
void CLASS ppg_interpolate_INDI(ushort(*image)[4], const unsigned filters,
const int width, const int height,
const int colors, void *dcraw, dcraw_data *h)
{
int dir[5] = { 1, width, -1, -width, 1 };
int row, col, diff[2] = { 0, 0 }, guess[2], c, d, i;
ushort(*pix)[4];
border_interpolate_INDI(height, width, image, filters, colors, 3, h);
dcraw_message(dcraw, DCRAW_VERBOSE, _("PPG interpolation...\n")); /*UF*/
#ifdef _OPENMP
#pragma omp parallel \
default(none) \
shared(image,dir,diff) \
private(row,col,i,d,c,pix,guess)
#endif
{
/* Fill in the green layer with gradients and pattern recognition: */
#ifdef _OPENMP
#pragma omp for
#endif
for (row = 3; row < height - 3; row++) {
for (col = 3 + (FC(row, 3) & 1), c = FC(row, col); col < width - 3; col += 2) {
pix = image + row * width + col;
for (i = 0; (d = dir[i]) > 0; i++) {
guess[i] = (pix[-d][1] + pix[0][c] + pix[d][1]) * 2
- pix[-2 * d][c] - pix[2 * d][c];
diff[i] = (ABS(pix[-2 * d][c] - pix[ 0][c]) +
ABS(pix[ 2 * d][c] - pix[ 0][c]) +
ABS(pix[ -d][1] - pix[ d][1])) * 3 +
(ABS(pix[ 3 * d][1] - pix[ d][1]) +
ABS(pix[-3 * d][1] - pix[-d][1])) * 2;
}
d = dir[i = diff[0] > diff[1]];
pix[0][1] = ULIM(guess[i] >> 2, pix[d][1], pix[-d][1]);
}
}
/* Calculate red and blue for each green pixel: */
#ifdef _OPENMP
#pragma omp for
#endif
for (row = 1; row < height - 1; row++) {
for (col = 1 + (FC(row, 2) & 1), c = FC(row, col + 1); col < width - 1; col += 2) {
pix = image + row * width + col;
for (i = 0; (d = dir[i]) > 0; c = 2 - c, i++)
pix[0][c] = CLIP((pix[-d][c] + pix[d][c] + 2 * pix[0][1]
- pix[-d][1] - pix[d][1]) >> 1);
}
}
/* Calculate blue for red pixels and vice versa: */
#ifdef _OPENMP
#pragma omp for
#endif
for (row = 1; row < height - 1; row++) {
for (col = 1 + (FC(row, 1) & 1), c = 2 - FC(row, col); col < width - 1; col += 2) {
pix = image + row * width + col;
for (i = 0; (d = dir[i] + dir[i + 1]) > 0; i++) {
diff[i] = ABS(pix[-d][c] - pix[d][c]) +
ABS(pix[-d][1] - pix[0][1]) +
ABS(pix[ d][1] - pix[0][1]);
guess[i] = pix[-d][c] + pix[d][c] + 2 * pix[0][1]
- pix[-d][1] - pix[d][1];
}
if (diff[0] != diff[1])
pix[0][c] = CLIP(guess[diff[0] > diff[1]] >> 1);
else
pix[0][c] = CLIP((guess[0] + guess[1]) >> 2);
}
}
}
}
void CLASS cielab_INDI(ushort rgb[3], short lab[3], const int colors,
const float rgb_cam[3][4])
{
int c, i, j, k;
float r, xyz[3];
static float cbrt[0x10000], xyz_cam[3][4];
if (!rgb) {
for (i = 0; i < 0x10000; i++) {
r = i / 65535.0;
cbrt[i] = r > 0.008856 ? pow(r, (float)(1 / 3.0)) : 7.787 * r + 16 / 116.0;
}
for (i = 0; i < 3; i++)
for (j = 0; j < colors; j++)
for (xyz_cam[i][j] = k = 0; k < 3; k++)
xyz_cam[i][j] += xyz_rgb[i][k] * rgb_cam[k][j] / d65_white[i];
return;
}
xyz[0] = xyz[1] = xyz[2] = 0.5;
FORCC {
xyz[0] += xyz_cam[0][c] * rgb[c];
xyz[1] += xyz_cam[1][c] * rgb[c];
xyz[2] += xyz_cam[2][c] * rgb[c];
}
xyz[0] = cbrt[CLIP((int) xyz[0])];
xyz[1] = cbrt[CLIP((int) xyz[1])];
xyz[2] = cbrt[CLIP((int) xyz[2])];
lab[0] = 64 * (116 * xyz[1] - 16);
lab[1] = 64 * 500 * (xyz[0] - xyz[1]);
lab[2] = 64 * 200 * (xyz[1] - xyz[2]);
}
#define TS 512 /* Tile Size */
/*
Frank Markesteijn's algorithm for Fuji X-Trans sensors
*/
void CLASS xtrans_interpolate_INDI(ushort(*image)[4], const unsigned filters,
const int width, const int height,
const int colors, const float rgb_cam[3][4],
void *dcraw, dcraw_data *hh, const int passes)
{
int c, d, f, g, h, i, v, ng, row, col, top, left, mrow, mcol;
int val, ndir, pass, hm[8], avg[4], color[3][8];
static const short orth[12] = { 1, 0, 0, 1, -1, 0, 0, -1, 1, 0, 0, 1 },
patt[2][16] = { { 0, 1, 0, -1, 2, 0, -1, 0, 1, 1, 1, -1, 0, 0, 0, 0 },
{ 0, 1, 0, -2, 1, 0, -2, 0, 1, 1, -2, -2, 1, -1, -1, 1 }
},
dir[4] = { 1, TS, TS + 1, TS - 1 };
short allhex[3][3][2][8], *hex;
ushort min, max, sgrow = 0, sgcol = 0;
ushort(*rgb)[TS][TS][3], (*rix)[3], (*pix)[4];
short(*lab) [TS][3], (*lix)[3];
float(*drv)[TS][TS], diff[6], tr;
char(*homo)[TS][TS], *buffer;
dcraw_message(dcraw, DCRAW_VERBOSE, _("%d-pass X-Trans interpolation...\n"), passes); /*NKBJ*/
cielab_INDI(0, 0, colors, rgb_cam);
border_interpolate_INDI(height, width, image, filters, colors, 6, hh);
ndir = 4 << (passes > 1);
/* Map a green hexagon around each non-green pixel and vice versa: */
for (row = 0; row < 3; row++)
for (col = 0; col < 3; col++)
for (ng = d = 0; d < 10; d += 2) {
g = fcol_INDI(filters, row, col, hh->top_margin, hh->left_margin, hh->xtrans) == 1;
if (fcol_INDI(filters, row + orth[d], col + orth[d + 2], hh->top_margin, hh->left_margin, hh->xtrans) == 1) ng = 0;
else ng++;
if (ng == 4) {
sgrow = row;
sgcol = col;
}
if (ng == g + 1) FORC(8) {
v = orth[d ] * patt[g][c * 2] + orth[d + 1] * patt[g][c * 2 + 1];
h = orth[d + 2] * patt[g][c * 2] + orth[d + 3] * patt[g][c * 2 + 1];
allhex[row][col][0][c ^ (g * 2 & d)] = h + v * width;
allhex[row][col][1][c ^ (g * 2 & d)] = h + v * TS;
}
}
/* Set green1 and green3 to the minimum and maximum allowed values: */
for (row = 2; row < height - 2; row++)
for (min = ~(max = 0), col = 2; col < width - 2; col++) {
if (fcol_INDI(filters, row, col, hh->top_margin, hh->left_margin, hh->xtrans) == 1 && (min = ~(max = 0))) continue;
pix = image + row * width + col;
hex = allhex[row % 3][col % 3][0];
if (!max) FORC(6) {
val = pix[hex[c]][1];
if (min > val) min = val;
if (max < val) max = val;
}
pix[0][1] = min;
pix[0][3] = max;
switch ((row - sgrow) % 3) {
case 1:
if (row < height - 3) {
row++;
col--;
}
break;
case 2:
if ((min = ~(max = 0)) && (col += 2) < width - 3 && row > 2) row--;
}
}
#ifdef _OPENMP
#pragma omp parallel \
default(shared) \
private(top, left, row, col, pix, mrow, mcol, hex, color, c, pass, rix, val, d, f, g, h, i, diff, lix, tr, avg, v, buffer, rgb, lab, drv, homo, hm, max)
#endif
{
buffer = (char *) malloc(TS * TS * (ndir * 11 + 6));
merror(buffer, "xtrans_interpolate()");
rgb = (ushort(*)[TS][TS][3]) buffer;
lab = (short(*) [TS][3])(buffer + TS * TS * (ndir * 6));
drv = (float(*)[TS][TS])(buffer + TS * TS * (ndir * 6 + 6));
homo = (char(*)[TS][TS])(buffer + TS * TS * (ndir * 10 + 6));
progress(PROGRESS_INTERPOLATE, -height);
#ifdef _OPENMP
#pragma omp for
#endif
for (top = 3; top < height - 19; top += TS - 16) {
progress(PROGRESS_INTERPOLATE, TS - 16);
for (left = 3; left < width - 19; left += TS - 16) {
mrow = MIN(top + TS, height - 3);
mcol = MIN(left + TS, width - 3);
for (row = top; row < mrow; row++)
for (col = left; col < mcol; col++)
memcpy(rgb[0][row - top][col - left], image[row * width + col], 6);
FORC3 memcpy(rgb[c + 1], rgb[0], sizeof * rgb);
/* Interpolate green horizontally, vertically, and along both diagonals: */
for (row = top; row < mrow; row++)
for (col = left; col < mcol; col++) {
if ((f = fcol_INDI(filters, row, col, hh->top_margin, hh->left_margin, hh->xtrans)) == 1) continue;
pix = image + row * width + col;
hex = allhex[row % 3][col % 3][0];
color[1][0] = 174 * (pix[ hex[1]][1] + pix[ hex[0]][1]) -
46 * (pix[2 * hex[1]][1] + pix[2 * hex[0]][1]);
color[1][1] = 223 * pix[ hex[3]][1] + pix[ hex[2]][1] * 33 +
92 * (pix[ 0 ][f] - pix[ -hex[2]][f]);
FORC(2) color[1][2 + c] =
164 * pix[hex[4 + c]][1] + 92 * pix[-2 * hex[4 + c]][1] + 33 *
(2 * pix[0][f] - pix[3 * hex[4 + c]][f] - pix[-3 * hex[4 + c]][f]);
FORC4 rgb[c ^ !((row - sgrow) % 3)][row - top][col - left][1] =
LIM(color[1][c] >> 8, pix[0][1], pix[0][3]);
}
for (pass = 0; pass < passes; pass++) {
if (pass == 1)
memcpy(rgb += 4, buffer, 4 * sizeof * rgb);
/* Recalculate green from interpolated values of closer pixels: */
if (pass) {
for (row = top + 2; row < mrow - 2; row++)
for (col = left + 2; col < mcol - 2; col++) {
if ((f = fcol_INDI(filters, row, col, hh->top_margin, hh->left_margin, hh->xtrans)) == 1) continue;
pix = image + row * width + col;
hex = allhex[row % 3][col % 3][1];
for (d = 3; d < 6; d++) {
rix = &rgb[(d - 2) ^ !((row - sgrow) % 3)][row - top][col - left];
val = rix[-2 * hex[d]][1] + 2 * rix[hex[d]][1]
- rix[-2 * hex[d]][f] - 2 * rix[hex[d]][f] + 3 * rix[0][f];
rix[0][1] = LIM(val / 3, pix[0][1], pix[0][3]);
}
}
}
/* Interpolate red and blue values for solitary green pixels: */
for (row = (top - sgrow + 4) / 3 * 3 + sgrow; row < mrow - 2; row += 3)
for (col = (left - sgcol + 4) / 3 * 3 + sgcol; col < mcol - 2; col += 3) {
rix = &rgb[0][row - top][col - left];
h = fcol_INDI(filters, row, col + 1, hh->top_margin, hh->left_margin, hh->xtrans);
memset(diff, 0, sizeof diff);
for (i = 1, d = 0; d < 6; d++, i ^= TS ^ 1, h ^= 2) {
for (c = 0; c < 2; c++, h ^= 2) {
g = 2 * rix[0][1] - rix[i << c][1] - rix[-i << c][1];
color[h][d] = g + rix[i << c][h] + rix[-i << c][h];
if (d > 1)
diff[d] += SQR(rix[i << c][1] - rix[-i << c][1]
- rix[i << c][h] + rix[-i << c][h]) + SQR(g);
}
if (d > 1 && (d & 1))
if (diff[d - 1] < diff[d])
FORC(2) color[c * 2][d] = color[c * 2][d - 1];
if (d < 2 || (d & 1)) {
FORC(2) rix[0][c * 2] = CLIP(color[c * 2][d] / 2);
rix += TS * TS;
}
}
}
/* Interpolate red for blue pixels and vice versa: */
for (row = top + 1; row < mrow - 1; row++)
for (col = left + 1; col < mcol - 1; col++) {
if ((f = 2 - fcol_INDI(filters, row, col, hh->top_margin, hh->left_margin, hh->xtrans)) == 1) continue;
rix = &rgb[0][row - top][col - left];
i = (row - sgrow) % 3 ? TS : 1;
for (d = 0; d < 4; d++, rix += TS * TS)
rix[0][f] = CLIP((rix[i][f] + rix[-i][f] +
2 * rix[0][1] - rix[i][1] - rix[-i][1]) / 2);
}
/* Fill in red and blue for 2x2 blocks of green: */
for (row = top + 2; row < mrow - 2; row++) if ((row - sgrow) % 3)
for (col = left + 2; col < mcol - 2; col++) if ((col - sgcol) % 3) {
rix = &rgb[0][row - top][col - left];
hex = allhex[row % 3][col % 3][1];
for (d = 0; d < ndir; d += 2, rix += TS * TS)
if (hex[d] + hex[d + 1]) {
g = 3 * rix[0][1] - 2 * rix[hex[d]][1] - rix[hex[d + 1]][1];
for (c = 0; c < 4; c += 2) rix[0][c] =
CLIP((g + 2 * rix[hex[d]][c] + rix[hex[d + 1]][c]) / 3);
} else {
g = 2 * rix[0][1] - rix[hex[d]][1] - rix[hex[d + 1]][1];
for (c = 0; c < 4; c += 2) rix[0][c] =
CLIP((g + rix[hex[d]][c] + rix[hex[d + 1]][c]) / 2);
}
}
}
rgb = (ushort(*)[TS][TS][3]) buffer;
mrow -= top;
mcol -= left;
/* Convert to CIELab and differentiate in all directions: */
for (d = 0; d < ndir; d++) {
for (row = 2; row < mrow - 2; row++)
for (col = 2; col < mcol - 2; col++)
cielab_INDI(rgb[d][row][col], lab[row][col], colors, rgb_cam);
for (f = dir[d & 3], row = 3; row < mrow - 3; row++)
for (col = 3; col < mcol - 3; col++) {
lix = &lab[row][col];
g = 2 * lix[0][0] - lix[f][0] - lix[-f][0];
drv[d][row][col] = SQR(g)
+ SQR((2 * lix[0][1] - lix[f][1] - lix[-f][1] + g * 500 / 232))
+ SQR((2 * lix[0][2] - lix[f][2] - lix[-f][2] - g * 500 / 580));
}
}
/* Build homogeneity maps from the derivatives: */
memset(homo, 0, ndir * TS * TS);
for (row = 4; row < mrow - 4; row++)
for (col = 4; col < mcol - 4; col++) {
for (tr = FLT_MAX, d = 0; d < ndir; d++)
if (tr > drv[d][row][col])
tr = drv[d][row][col];
tr *= 8;
for (d = 0; d < ndir; d++)
for (v = -1; v <= 1; v++)
for (h = -1; h <= 1; h++)
if (drv[d][row + v][col + h] <= tr)
homo[d][row][col]++;
}
/* Average the most homogenous pixels for the final result: */
if (height - top < TS + 4) mrow = height - top + 2;
if (width - left < TS + 4) mcol = width - left + 2;
for (row = MIN(top, 8); row < mrow - 8; row++)
for (col = MIN(left, 8); col < mcol - 8; col++) {
for (d = 0; d < ndir; d++)
for (hm[d] = 0, v = -2; v <= 2; v++)
for (h = -2; h <= 2; h++)
hm[d] += homo[d][row + v][col + h];
for (d = 0; d < ndir - 4; d++)
if (hm[d] < hm[d + 4]) hm[d ] = 0;
else if (hm[d] > hm[d + 4]) hm[d + 4] = 0;
for (max = hm[0], d = 1; d < ndir; d++)
if (max < hm[d]) max = hm[d];
max -= max >> 3;
memset(avg, 0, sizeof avg);
for (d = 0; d < ndir; d++)
if (hm[d] >= max) {
FORC3 avg[c] += rgb[d][row][col][c];
avg[3]++;
}
FORC3 image[(row + top)*width + col + left][c] = avg[c] / avg[3];
}
}
}
free(buffer);
} /* _OPENMP */
}
/*
Adaptive Homogeneity-Directed interpolation is based on
the work of Keigo Hirakawa, Thomas Parks, and Paul Lee.
*/
void CLASS ahd_interpolate_INDI(ushort(*image)[4], const unsigned filters,
const int width, const int height,
const int colors, const float rgb_cam[3][4],
void *dcraw, dcraw_data *h)
{
int i, j, top, left, row, col, tr, tc, c, d, val, hm[2];
static const int dir[4] = { -1, 1, -TS, TS };
unsigned ldiff[2][4], abdiff[2][4], leps, abeps;
ushort(*rgb)[TS][TS][3], (*rix)[3], (*pix)[4];
short(*lab)[TS][TS][3], (*lix)[3];
char(*homo)[TS][TS], *buffer;
dcraw_message(dcraw, DCRAW_VERBOSE, _("AHD interpolation...\n")); /*UF*/
#ifdef _OPENMP
#pragma omp parallel \
default(shared) \
private(top, left, row, col, pix, rix, lix, c, val, d, tc, tr, i, j, ldiff, abdiff, leps, abeps, hm, buffer, rgb, lab, homo)
#endif
{
cielab_INDI(0, 0, colors, rgb_cam);
border_interpolate_INDI(height, width, image, filters, colors, 5, h);
buffer = (char *) malloc(26 * TS * TS);
merror(buffer, "ahd_interpolate()");
rgb = (ushort(*)[TS][TS][3]) buffer;
lab = (short(*)[TS][TS][3])(buffer + 12 * TS * TS);
homo = (char(*)[TS][TS])(buffer + 24 * TS * TS);
progress(PROGRESS_INTERPOLATE, -height);
#ifdef _OPENMP
#pragma omp for
#endif
for (top = 2; top < height - 5; top += TS - 6) {
progress(PROGRESS_INTERPOLATE, TS - 6);
for (left = 2; left < width - 5; left += TS - 6) {
/* Interpolate green horizontally and vertically: */
for (row = top; row < top + TS && row < height - 2; row++) {
col = left + (FC(row, left) & 1);
for (c = FC(row, col); col < left + TS && col < width - 2; col += 2) {
pix = image + row * width + col;
val = ((pix[-1][1] + pix[0][c] + pix[1][1]) * 2
- pix[-2][c] - pix[2][c]) >> 2;
rgb[0][row - top][col - left][1] = ULIM(val, pix[-1][1], pix[1][1]);
val = ((pix[-width][1] + pix[0][c] + pix[width][1]) * 2
- pix[-2 * width][c] - pix[2 * width][c]) >> 2;
rgb[1][row - top][col - left][1] = ULIM(val, pix[-width][1], pix[width][1]);
}
}
/* Interpolate red and blue, and convert to CIELab: */
for (d = 0; d < 2; d++)
for (row = top + 1; row < top + TS - 1 && row < height - 3; row++)
for (col = left + 1; col < left + TS - 1 && col < width - 3; col++) {
pix = image + row * width + col;
rix = &rgb[d][row - top][col - left];
lix = &lab[d][row - top][col - left];
if ((c = 2 - FC(row, col)) == 1) {
c = FC(row + 1, col);
val = pix[0][1] + ((pix[-1][2 - c] + pix[1][2 - c]
- rix[-1][1] - rix[1][1]) >> 1);
rix[0][2 - c] = CLIP(val);
val = pix[0][1] + ((pix[-width][c] + pix[width][c]
- rix[-TS][1] - rix[TS][1]) >> 1);
} else
val = rix[0][1] + ((pix[-width - 1][c] + pix[-width + 1][c]
+ pix[+width - 1][c] + pix[+width + 1][c]
- rix[-TS - 1][1] - rix[-TS + 1][1]
- rix[+TS - 1][1] - rix[+TS + 1][1] + 1) >> 2);
rix[0][c] = CLIP(val);
c = FC(row, col);
rix[0][c] = pix[0][c];
cielab_INDI(rix[0], lix[0], colors, rgb_cam);
}
/* Build homogeneity maps from the CIELab images: */
memset(homo, 0, 2 * TS * TS);
for (row = top + 2; row < top + TS - 2 && row < height - 4; row++) {
tr = row - top;
for (col = left + 2; col < left + TS - 2 && col < width - 4; col++) {
tc = col - left;
for (d = 0; d < 2; d++) {
lix = &lab[d][tr][tc];
for (i = 0; i < 4; i++) {
ldiff[d][i] = ABS(lix[0][0] - lix[dir[i]][0]);
abdiff[d][i] = SQR(lix[0][1] - lix[dir[i]][1])
+ SQR(lix[0][2] - lix[dir[i]][2]);
}
}
leps = MIN(MAX(ldiff[0][0], ldiff[0][1]),
MAX(ldiff[1][2], ldiff[1][3]));
abeps = MIN(MAX(abdiff[0][0], abdiff[0][1]),
MAX(abdiff[1][2], abdiff[1][3]));
for (d = 0; d < 2; d++)
for (i = 0; i < 4; i++)
if (ldiff[d][i] <= leps && abdiff[d][i] <= abeps)
homo[d][tr][tc]++;
}
}
/* Combine the most homogenous pixels for the final result: */
for (row = top + 3; row < top + TS - 3 && row < height - 5; row++) {
tr = row - top;
for (col = left + 3; col < left + TS - 3 && col < width - 5; col++) {
tc = col - left;
for (d = 0; d < 2; d++)
for (hm[d] = 0, i = tr - 1; i <= tr + 1; i++)
for (j = tc - 1; j <= tc + 1; j++)
hm[d] += homo[d][i][j];
if (hm[0] != hm[1])
FORC3 image[row * width + col][c] = rgb[hm[1] > hm[0]][tr][tc][c];
else
FORC3 image[row * width + col][c] =
(rgb[0][tr][tc][c] + rgb[1][tr][tc][c]) >> 1;
}
}
}
}
free(buffer);
} /* _OPENMP */
}
#undef TS
#define DTOP(x) ((x>65535) ? (unsigned short)65535 : (x<0) ? (unsigned short)0 : (unsigned short) x)
/*
* MG - This comment applies to the 3x3 optimized median function
*
* The following routines have been built from knowledge gathered
* around the Web. I am not aware of any copyright problem with
* them, so use it as you want.
* N. Devillard - 1998
*/
#define PIX_SORT(a,b) { if ((a)>(b)) PIX_SWAP((a),(b)); }
#define PIX_SWAP(a,b) { int temp=(a);(a)=(b);(b)=temp; }
static inline int median9(int *p)
{
PIX_SORT(p[1], p[2]) ;
PIX_SORT(p[4], p[5]) ;
PIX_SORT(p[7], p[8]) ;
PIX_SORT(p[0], p[1]) ;
PIX_SORT(p[3], p[4]) ;
PIX_SORT(p[6], p[7]) ;
PIX_SORT(p[1], p[2]) ;
PIX_SORT(p[4], p[5]) ;
PIX_SORT(p[7], p[8]) ;
PIX_SORT(p[0], p[3]) ;
PIX_SORT(p[5], p[8]) ;
PIX_SORT(p[4], p[7]) ;
PIX_SORT(p[3], p[6]) ;
PIX_SORT(p[1], p[4]) ;
PIX_SORT(p[2], p[5]) ;
PIX_SORT(p[4], p[7]) ;
PIX_SORT(p[4], p[2]) ;
PIX_SORT(p[6], p[4]) ;
PIX_SORT(p[4], p[2]) ;
return (p[4]) ;
}
#undef PIX_SWAP
#undef PIX_SORT
// Just making this function inline speeds up ahd_interpolate_INDI() up to 15%
static inline ushort eahd_median(int row, int col, int color,
ushort(*image)[4], const int width)
{
//declare the pixel array
int pArray[9];
int result;
//perform the median filter (this only works for red or blue)
// result = median(R-G)+G or median(B-G)+G
//
// to perform the filter on green, it needs to be the average
// results = (median(G-R)+median(G-B)+R+B)/2
//no checks are done here to speed up the inlining
pArray[0] = image[width * (row) + col + 1][color] - image[width * (row) + col + 1][1];
pArray[1] = image[width * (row - 1) + col + 1][color] - image[width * (row - 1) + col + 1][1];
pArray[2] = image[width * (row - 1) + col ][color] - image[width * (row - 1) + col ][1];
pArray[3] = image[width * (row - 1) + col - 1][color] - image[width * (row - 1) + col - 1][1];
pArray[4] = image[width * (row) + col - 1][color] - image[width * (row) + col - 1][1];
pArray[5] = image[width * (row + 1) + col - 1][color] - image[width * (row + 1) + col - 1][1];
pArray[6] = image[width * (row + 1) + col ][color] - image[width * (row + 1) + col ][1];
pArray[7] = image[width * (row + 1) + col + 1][color] - image[width * (row + 1) + col + 1][1];
pArray[8] = image[width * (row) + col ][color] - image[width * (row) + col ][1];
median9(pArray);
result = pArray[4] + image[width * (row) + col ][1];
return DTOP(result);
}
// Add the color smoothing from Kimmel as suggested in the AHD paper
// Algorithm updated by Michael Goertz
void CLASS color_smooth(ushort(*image)[4], const int width, const int height,
const int passes)
{
int row, col;
int row_start = 2;
int row_stop = height - 2;
int col_start = 2;
int col_stop = width - 2;
//interate through all the colors
int count;
ushort *mpix;
for (count = 0; count < passes; count++) {
//perform 3 iterations - seems to be a commonly settled upon number of iterations
#ifdef _OPENMP
#pragma omp parallel for default(shared) private(row,col,mpix)
#endif
for (row = row_start; row < row_stop; row++) {
for (col = col_start; col < col_stop; col++) {
//calculate the median only over the red and blue
//calculating over green seems to offer very little additional quality
mpix = image[row * width + col];
mpix[0] = eahd_median(row, col, 0, image, width);
mpix[2] = eahd_median(row, col, 2, image, width);
}
}
}
}
void CLASS fuji_rotate_INDI(ushort(**image_p)[4], int *height_p,
int *width_p, int *fuji_width_p, const int colors,
const double step, void *dcraw)
{
int height = *height_p, width = *width_p, fuji_width = *fuji_width_p; /*UF*/
ushort(*image)[4] = *image_p; /*UF*/
int i, row, col;
float r, c, fr, fc;
int ur, uc;
ushort wide, high, (*img)[4], (*pix)[4];
if (!fuji_width) return;
dcraw_message(dcraw, DCRAW_VERBOSE, _("Rotating image 45 degrees...\n"));
fuji_width = (fuji_width - 1/* + shrink*/)/* >> shrink*/;
wide = fuji_width / step;
high = (height - fuji_width) / step;
img = (ushort(*)[4]) calloc(wide * high, sizeof * img);
merror(img, "fuji_rotate()");
#ifdef _OPENMP
#pragma omp parallel for default(shared) private(row,col,ur,uc,r,c,fr,fc,pix,i)
#endif
for (row = 0; row < high; row++) {
for (col = 0; col < wide; col++) {
ur = r = fuji_width + (row - col) * step;
uc = c = (row + col) * step;
if (ur > height - 2 || uc > width - 2) continue;
fr = r - ur;
fc = c - uc;
pix = image + ur * width + uc;
for (i = 0; i < colors; i++)
img[row * wide + col][i] =
(pix[ 0][i] * (1 - fc) + pix[ 1][i] * fc) * (1 - fr) +
(pix[width][i] * (1 - fc) + pix[width + 1][i] * fc) * fr;
}
}
free(image);
width = wide;
height = high;
image = img;
fuji_width = 0;
*height_p = height; /* INDI - UF*/
*width_p = width;
*fuji_width_p = fuji_width;
*image_p = image;
}
void CLASS flip_image_INDI(ushort(*image)[4], int *height_p, int *width_p,
/*const*/ int flip) /*UF*/
{
unsigned *flag;
int size, base, dest, next, row, col;
gint64 *img, hold;
int height = *height_p, width = *width_p;/* INDI - UF*/
// Message is suppressed because error handling is not enabled here.
// dcraw_message (dcraw, DCRAW_VERBOSE,_("Flipping image %c:%c:%c...\n"),
// flip & 1 ? 'H':'0', flip & 2 ? 'V':'0', flip & 4 ? 'T':'0'); /*UF*/
img = (gint64 *) image;
size = height * width;
flag = calloc((size + 31) >> 5, sizeof * flag);
merror(flag, "flip_image()");
for (base = 0; base < size; base++) {
if (flag[base >> 5] & (1 << (base & 31)))
continue;
dest = base;
hold = img[base];
while (1) {
if (flip & 4) {
row = dest % height;
col = dest / height;
} else {
row = dest / width;
col = dest % width;
}
if (flip & 2)
row = height - 1 - row;
if (flip & 1)
col = width - 1 - col;
next = row * width + col;
if (next == base) break;
flag[next >> 5] |= 1 << (next & 31);
img[dest] = img[next];
dest = next;
}
img[dest] = hold;
}
free(flag);
if (flip & 4) SWAP(height, width);
*height_p = height; /* INDI - UF*/
*width_p = width;
}
|