/* * aptdec - A lightweight FOSS (NOAA) APT decoder * Copyright (C) 2004-2009 Thierry Leconte (F4DWV) 2019-2023 Xerbo (xerbo@protonmail.com) * * 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. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include #include #include #include #include #include "algebra.h" #include #include "util.h" #include "calibration.h" #define APT_COUNT_RATIO (1023.0f/255.0f) apt_image_t apt_image_clone(apt_image_t img) { apt_image_t _img = img; _img.data = (uint8_t *)malloc(APT_IMG_WIDTH * img.rows); memcpy(_img.data, img.data, APT_IMG_WIDTH * img.rows); return _img; } static void decode_telemetry(const float *data, size_t rows, size_t offset, float *wedges) { // Calculate row average float *telemetry_rows = (float *)malloc(rows * sizeof(float)); for (size_t y = 0; y < rows; y++) { telemetry_rows[y] = meanf(&data[y*APT_IMG_WIDTH + offset + APT_CH_WIDTH], APT_TELEMETRY_WIDTH); } // Calculate relative telemetry offset (via step detection, i.e. wedge 8 to 9) size_t telemetry_offset = 0; float max_difference = 0.0f; for (size_t y = APT_WEDGE_HEIGHT; y <= rows - APT_WEDGE_HEIGHT; y++) { float difference = sumf(&telemetry_rows[y - APT_WEDGE_HEIGHT], APT_WEDGE_HEIGHT) - sumf(&telemetry_rows[y], APT_WEDGE_HEIGHT); // Find the maximum difference if (difference > max_difference) { max_difference = difference; telemetry_offset = (y + 64) % APT_FRAME_LEN; } } // Find the least noisy frame (via standard deviation) float best_noise = FLT_MAX; size_t best_frame = 0; for (size_t y = telemetry_offset; y < rows; y += APT_FRAME_LEN) { float noise = 0.0f; for (size_t i = 0; i < APT_FRAME_WEDGES; i++) { noise += standard_deviation(&telemetry_rows[y + i*APT_WEDGE_HEIGHT], APT_WEDGE_HEIGHT); } if (noise < best_noise) { best_noise = noise; best_frame = y; } } for (size_t i = 0; i < APT_FRAME_WEDGES; i++) { wedges[i] = meanf(&telemetry_rows[best_frame + i*APT_WEDGE_HEIGHT], APT_WEDGE_HEIGHT); } free(telemetry_rows); } static float average_spc(apt_image_t *img, size_t offset) { float *rows = (float *)malloc(img->rows * sizeof(float)); float average = 0.0f; for (size_t y = 0; y < img->rows; y++) { float row_average = 0.0f; for (size_t x = 0; x < APT_SPC_WIDTH; x++) { row_average += img->data[y*APT_IMG_WIDTH + offset - APT_SPC_WIDTH + x]; } row_average /= (float)APT_SPC_WIDTH; rows[y] = row_average; average += row_average; } average /= (float)img->rows; float weighted_average = 0.0f; size_t n = 0; for (size_t y = 0; y < img->rows; y++) { if (fabsf(rows[y] - average) < 50.0f) { weighted_average += rows[y]; n++; } } free(rows); return weighted_average / (float)n; } apt_image_t apt_normalize(const float *data, size_t rows, apt_satellite_t satellite, int *error) { apt_image_t img; img.rows = rows; img.satellite = satellite; *error = 0; if (rows < APTDEC_NORMALIZE_ROWS) { *error = -1; return img; } // Decode and average wedges float wedges[APT_FRAME_WEDGES]; float wedges_cha[APT_FRAME_WEDGES]; float wedges_chb[APT_FRAME_WEDGES]; decode_telemetry(data, rows, APT_CHA_OFFSET, wedges_cha); decode_telemetry(data, rows, APT_CHB_OFFSET, wedges_chb); for (size_t i = 0; i < APT_FRAME_WEDGES; i++) { wedges[i] = (wedges_cha[i] + wedges_chb[i]) / 2.0f; } // Calculate normalization const float reference[9] = { 31, 63, 95, 127, 159, 191, 223, 255, 0 }; linear_t normalization = linear_regression(wedges, reference, 9); if (normalization.a < 0.0f) { *error = -1; return img; } // Normalize telemetry for (size_t i = 0; i < APT_FRAME_WEDGES; i++) { img.telemetry[0][i] = linear_calc(wedges_cha[i], normalization); img.telemetry[1][i] = linear_calc(wedges_chb[i], normalization); } // Decode channel ID wedges img.ch[0] = roundf(img.telemetry[0][15] / 32.0f); img.ch[1] = roundf(img.telemetry[1][15] / 32.0f); if (img.ch[0] < 1 || img.ch[0] > 6) img.ch[0] = AVHRR_CHANNEL_UNKNOWN; if (img.ch[1] < 1 || img.ch[1] > 6) img.ch[1] = AVHRR_CHANNEL_UNKNOWN; // Normalize and quantize image data img.data = (uint8_t *)malloc(rows * APT_IMG_WIDTH); for (size_t i = 0; i < rows * APT_IMG_WIDTH; i++) { float count = linear_calc(data[i], normalization); img.data[i] = clamp_int(roundf(count), 0, 255); } // Get space brightness img.space_view[0] = average_spc(&img, APT_CHA_OFFSET); img.space_view[1] = average_spc(&img, APT_CHB_OFFSET); return img; } static void make_thermal_lut(apt_image_t *img, avhrr_channel_t ch, int satellite, float *lut) { ch -= 4; const calibration_t calibration = get_calibration(satellite); const float Ns = calibration.cor[ch].Ns; const float Vc = calibration.rad[ch].vc; const float A = calibration.rad[ch].A; const float B = calibration.rad[ch].B; // Compute PRT temperature float T[4]; for (size_t n = 0; n < 4; n++) { T[n] = quadratic_calc(img->telemetry[1][n + 9] * APT_COUNT_RATIO, calibration.prt[n]); } float Tbb = meanf(T, 4); // Blackbody temperature float Tbbstar = A + Tbb * B; // Effective blackbody temperature float Nbb = C1 * pow(Vc, 3) / (expf(C2 * Vc / Tbbstar) - 1.0f); // Blackbody radiance float Cs = img->space_view[1] * APT_COUNT_RATIO; float Cb = img->telemetry[1][14] * APT_COUNT_RATIO; for (size_t i = 0; i < 256; i++) { float Nl = Ns + (Nbb - Ns) * (Cs - i * APT_COUNT_RATIO) / (Cs - Cb); // Linear radiance estimate float Nc = quadratic_calc(Nl, calibration.cor[ch].quadratic); // Non-linear correction float Ne = Nl + Nc; // Corrected radiance float Testar = C2 * Vc / logf(C1 * powf(Vc, 3) / Ne + 1.0); // Equivalent black body temperature float Te = (Testar - A) / B; // Temperature (kelvin) // Convert to celsius lut[i] = Te - 273.15; } } int apt_calibrate_thermal(apt_image_t *img, apt_region_t region) { if (img->ch[1] != AVHRR_CHANNEL_4 && img->ch[1] != AVHRR_CHANNEL_5 && img->ch[1] != AVHRR_CHANNEL_3B) { return 1; } float lut[256]; make_thermal_lut(img, img->ch[1], img->satellite, lut); for (size_t y = 0; y < img->rows; y++) { for (size_t x = 0; x < region.width; x++) { float temperature = lut[img->data[y * APT_IMG_WIDTH + region.offset + x]]; img->data[y * APT_IMG_WIDTH + region.offset + x] = clamp_int(roundf((temperature + 100.0) / 160.0 * 255.0), 0, 255); } } return 0; } static float calibrate_pixel_visible(float value, int channel, calibration_t cal) { if (value > cal.visible[channel].cutoff) { return linear_calc(value * APT_COUNT_RATIO, cal.visible[channel].high) / 100.0f * 255.0f; } else { return linear_calc(value * APT_COUNT_RATIO, cal.visible[channel].low) / 100.0f * 255.0f; } } int apt_calibrate_visible(apt_image_t *img, apt_region_t region) { if (img->ch[0] != AVHRR_CHANNEL_1 && img->ch[0] != AVHRR_CHANNEL_2) { return 1; } calibration_t calibration = get_calibration(img->satellite); for (size_t y = 0; y < img->rows; y++) { for (size_t x = 0; x < region.width; x++) { float albedo = calibrate_pixel_visible(img->data[y * APT_IMG_WIDTH + region.offset + x], img->ch[0]-1, calibration); img->data[y * APT_IMG_WIDTH + region.offset + x] = clamp_int(roundf(albedo), 0, 255); } } return 0; }