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image.c 9.6 KiB

21 년 전
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  1. /*
  2. * This file is part of Aptdec.
  3. * Copyright (c) 2004-2009 Thierry Leconte (F4DWV), Xerbo (xerbo@protonmail.com) 2019-2020
  4. *
  5. * Aptdec is free software: you can redistribute it and/or modify
  6. * it under the terms of the GNU General Public License as published by
  7. * the Free Software Foundation, either version 2 of the License, or
  8. * (at your option) any later version.
  9. *
  10. * This program is distributed in the hope that it will be useful,
  11. * but WITHOUT ANY WARRANTY; without even the implied warranty of
  12. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  13. * GNU General Public License for more details.
  14. *
  15. * You should have received a copy of the GNU General Public License
  16. * along with this program. If not, see <https://www.gnu.org/licenses/>.
  17. *
  18. */
  19. #include <stdio.h>
  20. #include <string.h>
  21. #include <sndfile.h>
  22. #include <math.h>
  23. #include <stdlib.h>
  24. #include "offsets.h"
  25. #include "messages.h"
  26. #define REGORDER 3
  27. typedef struct {
  28. double cf[REGORDER + 1];
  29. } rgparam_t;
  30. typedef struct {
  31. float *prow[MAX_HEIGHT]; // Row buffers
  32. int nrow; // Number of rows
  33. int chA, chB; // ID of each channel
  34. char name[256]; // Stripped filename
  35. } image_t;
  36. typedef struct {
  37. char *type; // Output image type
  38. char *effects;
  39. int satnum; // The satellite number
  40. char *map; // Path to a map file
  41. char *path; // Output directory
  42. int realtime;
  43. } options_t;
  44. extern void polyreg(const int m, const int n, const double x[], const double y[], double c[]);
  45. // Compute regression
  46. static void rgcomp(double x[16], rgparam_t * rgpr) {
  47. // { 0.106, 0.215, 0.324, 0.433, 0.542, 0.652, 0.78, 0.87, 0.0 }
  48. const double y[9] = { 31.07, 63.02, 94.96, 126.9, 158.86, 191.1, 228.62, 255.0, 0.0 };
  49. polyreg(REGORDER, 9, x, y, rgpr -> cf);
  50. }
  51. // Convert a value to 0-255 based off the provided regression curve
  52. static double rgcal(float x, rgparam_t *rgpr) {
  53. double y, p;
  54. int i;
  55. for (i = 0, y = 0.0, p = 1.0; i < REGORDER + 1; i++) {
  56. y += rgpr->cf[i] * p;
  57. p = p * x;
  58. }
  59. return(y);
  60. }
  61. static double tele[16];
  62. static double Cs;
  63. void histogramEqualise(float **prow, int nrow, int offset, int width){
  64. // Plot histogram
  65. int histogram[256] = { 0 };
  66. for(int y = 0; y < nrow; y++)
  67. for(int x = 0; x < width; x++)
  68. histogram[(int)floor(prow[y][x+offset])]++;
  69. // Find min/max points
  70. int min = -1, max = -1;
  71. for(int i = 5; i < 250; i++){
  72. if(histogram[i]/width/(nrow/255.0) > 0.2){
  73. if(min == -1)
  74. min = i;
  75. max = i;
  76. }
  77. }
  78. //printf("Column %i-%i: Min: %i, Max %i\n", offset, offset+width, min, max);
  79. // Spread values to avoid overshoot
  80. min -= 5; max += 5;
  81. // Stretch the brightness into the new range
  82. for(int y = 0; y < nrow; y++)
  83. for(int x = 0; x < width; x++)
  84. prow[y][x+offset] = CLIP((prow[y][x+offset]-min) / (max-min) * 255.0, 0, 255);
  85. }
  86. // Brightness calibrate, including telemetry
  87. void calibrateImage(float **prow, int nrow, int offset, int width, rgparam_t regr){
  88. offset -= SYNC_WIDTH+SPC_WIDTH;
  89. for (int n = 0; n < nrow; n++) {
  90. float *pixelv = prow[n];
  91. for (int i = 0; i < width+SYNC_WIDTH+SPC_WIDTH+TELE_WIDTH; i++) {
  92. float pv = rgcal(pixelv[i + offset], &regr);
  93. pixelv[i + offset] = CLIP(pv, 0, 255);
  94. }
  95. }
  96. }
  97. double teleNoise(double wedges[16]){
  98. int pattern[9] = { 31, 63, 95, 127, 159, 191, 223, 255, 0 };
  99. double noise = 0;
  100. for(int i = 0; i < 9; i++)
  101. noise += fabs(wedges[i] - (double)pattern[i]);
  102. return noise;
  103. }
  104. // Get telemetry data for thermal calibration/equalization
  105. int calibrate(float **prow, int nrow, int offset, int width) {
  106. double teleline[MAX_HEIGHT] = { 0.0 };
  107. double wedge[16];
  108. rgparam_t regr[30];
  109. int telestart, mtelestart = 0;
  110. int channel = -1;
  111. // The minimum rows required to decode a full frame
  112. if (nrow < 192) {
  113. fprintf(stderr, ERR_TELE_ROW);
  114. return 0;
  115. }
  116. // Calculate average of a row of telemetry
  117. for (int n = 0; n < nrow; n++) {
  118. float *pixelv = prow[n];
  119. // Average the center 40px
  120. for (int i = 3; i < 43; i++)
  121. teleline[n] += pixelv[i + offset + width];
  122. teleline[n] /= 40.0;
  123. }
  124. /* Wedge 7 is white and 8 is black, this will have the largest
  125. * difference in brightness, this will always be in the center of
  126. * the frame and can thus be used to find the start of the frame
  127. */
  128. double max = 0.0;
  129. for (int n = nrow / 3 - 64; n < 2 * nrow / 3 - 64; n++) {
  130. float df;
  131. // (sum 4px below) / (sum 4px above)
  132. df = (teleline[n - 4] + teleline[n - 3] + teleline[n - 2] + teleline[n - 1]) /
  133. (teleline[n + 0] + teleline[n + 1] + teleline[n + 2] + teleline[n + 3]);
  134. // Find the maximum difference
  135. if (df > max) {
  136. mtelestart = n;
  137. max = df;
  138. }
  139. }
  140. // Find the start of the first frame
  141. telestart = (mtelestart - FRAME_LEN/2) % FRAME_LEN;
  142. // Make sure that theres at least one full frame in the image
  143. if (nrow < telestart + FRAME_LEN) {
  144. fprintf(stderr, ERR_TELE_ROW);
  145. return(0);
  146. }
  147. // Find the least noisy frame
  148. double minNoise = -1;
  149. int bestFrame = telestart;
  150. for (int n = telestart, k = 0; n < nrow - FRAME_LEN; n += FRAME_LEN, k++) {
  151. // Turn pixels into wedge values
  152. for (int j = 0; j < 16; j++) {
  153. wedge[j] = 0.0;
  154. // Average the middle 6px
  155. for (int i = 1; i < 7; i++)
  156. wedge[j] += teleline[(j * 8) + i + n];
  157. wedge[j] /= 6;
  158. }
  159. double noise = teleNoise(wedge);
  160. if(noise < minNoise || minNoise == -1){
  161. minNoise = noise;
  162. bestFrame = k;
  163. // Compute & apply regression on the wedges
  164. rgcomp(wedge, &regr[k]);
  165. for (int j = 0; j < 16; j++)
  166. tele[j] = rgcal(wedge[j], &regr[k]);
  167. /* Compare the channel ID wedge to the reference
  168. * wedges, the wedge with the closest match will
  169. * be the channel ID
  170. */
  171. float min = -1;
  172. for (int j = 0; j < 6; j++) {
  173. float df = tele[15] - tele[j];
  174. df *= df;
  175. if (df < min || min == -1) {
  176. channel = j;
  177. min = df;
  178. }
  179. }
  180. }
  181. }
  182. calibrateImage(prow, nrow, offset, width, regr[bestFrame]);
  183. return channel + 1;
  184. }
  185. // --- Temperature Calibration --- //
  186. #include "satcal.h"
  187. typedef struct {
  188. double Nbb;
  189. double Cs;
  190. double Cb;
  191. int ch;
  192. } tempparam_t;
  193. // IR channel temperature compensation
  194. static void tempcomp(double t[16], int ch, int satnum, tempparam_t *tpr) {
  195. double Tbb, T[4];
  196. double C;
  197. tpr -> ch = ch - 4;
  198. // Compute equivalent T blackbody temperature
  199. for (int n = 0; n < 4; n++) {
  200. float d0, d1, d2;
  201. C = t[9 + n] * 4.0;
  202. d0 = satcal[satnum].d[n][0];
  203. d1 = satcal[satnum].d[n][1];
  204. d2 = satcal[satnum].d[n][2];
  205. T[n] = d0;
  206. T[n] += d1 * C;
  207. C = C * C;
  208. T[n] += d2 * C;
  209. }
  210. Tbb = (T[0] + T[1] + T[2] + T[3]) / 4.0;
  211. Tbb = satcal[satnum].rad[tpr->ch].A + satcal[satnum].rad[tpr->ch].B * Tbb;
  212. // Compute radiance blackbody
  213. C = satcal[satnum].rad[tpr->ch].vc;
  214. tpr->Nbb = c1 * C * C * C / (expm1(c2 * C / Tbb));
  215. // Store count blackbody and space
  216. tpr->Cs = Cs * 4.0;
  217. tpr->Cb = t[14] * 4.0;
  218. }
  219. // IR channel temperature calibration
  220. static double tempcal(float Ce, int satnum, tempparam_t * rgpr) {
  221. double Nl, Nc, Ns, Ne;
  222. double T, vc;
  223. Ns = satcal[satnum].cor[rgpr->ch].Ns;
  224. Nl = Ns + (rgpr->Nbb - Ns) * (rgpr->Cs - Ce * 4.0) / (rgpr->Cs - rgpr->Cb);
  225. Nc = satcal[satnum].cor[rgpr->ch].b[0] +
  226. satcal[satnum].cor[rgpr->ch].b[1] * Nl +
  227. satcal[satnum].cor[rgpr->ch].b[2] * Nl * Nl;
  228. Ne = Nl + Nc;
  229. vc = satcal[satnum].rad[rgpr->ch].vc;
  230. T = c2 * vc / log1p(c1 * vc * vc * vc / Ne);
  231. T = (T - satcal[satnum].rad[rgpr->ch].A) / satcal[satnum].rad[rgpr->ch].B;
  232. // Rescale to 0-255 for -60'C to +40'C
  233. T = (T - 273.15 + 60.0) / 100.0 * 256.0;
  234. return(T);
  235. }
  236. // Temperature calibration wrapper
  237. void temperature(options_t *opts, image_t *img, int offset, int width){
  238. tempparam_t temp;
  239. printf("Temperature... ");
  240. fflush(stdout);
  241. tempcomp(tele, img->chB, opts->satnum - 15, &temp);
  242. for (int y = 0; y < img->nrow; y++) {
  243. float *pixelv = img->prow[y];
  244. for (int x = 0; x < width; x++) {
  245. float pv = tempcal(pixelv[x + offset], opts->satnum - 15, &temp);
  246. pixelv[x + offset] = CLIP(pv, 0, 255);
  247. }
  248. }
  249. printf("Done\n");
  250. }
  251. void distrib(options_t *opts, image_t *img, char *chid) {
  252. int max = 0;
  253. // Options
  254. options_t options;
  255. options.path = opts->path;
  256. // Image options
  257. image_t distrib;
  258. strcpy(distrib.name, img->name);
  259. distrib.nrow = 256;
  260. // Assign memory
  261. for(int i = 0; i < 256; i++)
  262. distrib.prow[i] = (float *) malloc(sizeof(float) * 256);
  263. for(int n = 0; n < img->nrow; n++) {
  264. float *pixelv = img->prow[n];
  265. for(int i = 0; i < CH_WIDTH; i++) {
  266. int y = CLIP((int)pixelv[i + CHA_OFFSET], 0, 255);
  267. int x = CLIP((int)pixelv[i + CHB_OFFSET], 0, 255);
  268. distrib.prow[y][x]++;
  269. if(distrib.prow[y][x] > max)
  270. max = distrib.prow[y][x];
  271. }
  272. }
  273. // Scale to 0-255
  274. for(int x = 0; x < 256; x++)
  275. for(int y = 0; y < 256; y++)
  276. distrib.prow[y][x] = distrib.prow[y][x] / max * 255.0;
  277. extern int ImageOut(options_t *opts, image_t *img, int offset, int width, char *desc, char *chid, char *palette);
  278. ImageOut(&options, &distrib, 0, 256, "Distribution", chid, NULL);
  279. }
  280. extern float quick_select(float arr[], int n);
  281. // Recursive biased median denoise
  282. #define TRIG_LEVEL 40
  283. void denoise(float **prow, int nrow, int offset, int width){
  284. for(int y = 2; y < nrow-2; y++){
  285. for(int x = offset+1; x < offset+width-1; x++){
  286. if(prow[y][x+1] - prow[y][x] > TRIG_LEVEL ||
  287. prow[y][x-1] - prow[y][x] > TRIG_LEVEL ||
  288. prow[y+1][x] - prow[y][x] > TRIG_LEVEL ||
  289. prow[y-1][x] - prow[y][x] > TRIG_LEVEL){
  290. prow[y][x] = quick_select((float[]){
  291. prow[y+2][x-1], prow[y+2][x], prow[y+2][x+1],
  292. prow[y+1][x-1], prow[y+1][x], prow[y+1][x+1],
  293. prow[y-1][x-1], prow[y-1][x], prow[y-1][x+1],
  294. prow[y-2][x-1], prow[y-2][x], prow[y-2][x+1]
  295. }, 12);
  296. }
  297. }
  298. }
  299. }
  300. #undef TRIG_LEVEL