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https://github.com/curioustorvald/tsvm.git
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more psychovisual model
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@@ -151,6 +151,7 @@ static const int QUALITY_CG[] = {240, 180, 120, 60, 30, 5};
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// psychovisual tuning parameters
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static const float ANISOTROPY_MULT[] = {1.8f, 1.6f, 1.4f, 1.2f, 1.0f, 1.0f};
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static const float ANISOTROPY_BIAS[] = {0.2f, 0.1f, 0.0f, 0.0f, 0.0f, 0.0f};
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static const float ANISOTROPY_BIAS_CHROMA[] = {0.4f, 0.3f, 0.2f, 0.1f, 0.0f, 0.0f};
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// DWT coefficient structure for each subband
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typedef struct {
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@@ -828,6 +829,10 @@ static float perceptual_model3_LL(int quality, int level) {
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return n / m;
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}
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static float perceptual_model3_chroma_basecurve(int quality, int level) {
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return 1.0f - (1.0f / (0.5f * quality * quality + 1.0f)) * (level - 4.0f); // just a line that passes (4,1)
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}
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// Get perceptual weight for specific subband - Data-driven model based on coefficient variance analysis
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static float get_perceptual_weight_model2(int level, int subband_type, int is_chroma, int max_levels) {
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// Psychovisual model based on DWT coefficient statistics and Human Visual System sensitivity
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@@ -897,10 +902,12 @@ static float get_perceptual_weight_model2(int level, int subband_type, int is_ch
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}
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#define FOUR_PIXEL_DETAILER 0.88f
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#define TWO_PIXEL_DETAILER 0.92f
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// level is one-based index
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static float get_perceptual_weight(tav_encoder_t *enc, int level, int subband_type, int is_chroma, int max_levels) {
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// Psychovisual model based on DWT coefficient statistics and Human Visual System sensitivity
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// strategy: JPEG quantisation table + real-world statistics from the encoded videos
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// strategy: more horizontal detail
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if (!is_chroma) {
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// LL subband - contains most image energy, preserve carefully
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if (subband_type == 0)
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@@ -914,42 +921,26 @@ static float get_perceptual_weight(tav_encoder_t *enc, int level, int subband_ty
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// HL subband - vertical details
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float HL = perceptual_model3_HL(enc->quality_level, LH);
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if (subband_type == 2)
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return HL * (level == 3 ? FOUR_PIXEL_DETAILER : 1.0f);
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return HL * (level == 2 ? TWO_PIXEL_DETAILER : level == 3 ? FOUR_PIXEL_DETAILER : 1.0f);
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// HH subband - diagonal details
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else return perceptual_model3_HH(LH, HL) * (level == 3 ? FOUR_PIXEL_DETAILER : 1.0f);
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else return perceptual_model3_HH(LH, HL) * (level == 2 ? TWO_PIXEL_DETAILER : level == 3 ? FOUR_PIXEL_DETAILER : 1.0f);
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} else {
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// CHROMA CHANNELS: Less critical for human perception, more aggressive quantization
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// strategy: mimic 4:2:2 chroma subsampling
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// strategy: more horizontal detail
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//// mimic 4:4:0 (you heard that right!) chroma subsampling (4:4:4 for higher q, 4:2:0 for lower q)
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//// because our eyes are apparently sensitive to horizontal chroma diff as well?
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float base = perceptual_model3_chroma_basecurve(enc->quality_level, level);
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if (subband_type == 0) { // LL chroma - still important but less than luma
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return 1.0f;
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if (level >= 6) return 0.8f; // Chroma LL6: Less critical than luma LL
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if (level >= 5) return 0.9f;
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return 1.0f;
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} else if (subband_type == 1) { // LH chroma - horizontal chroma details
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return 1.8f;
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if (level >= 6) return 1.0f;
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if (level >= 5) return 1.2f;
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if (level >= 4) return 1.4f;
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if (level >= 3) return 1.6f;
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if (level >= 2) return 1.8f;
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return 2.0f;
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return FCLAMP(base, 1.0f, 100.0f);
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} else if (subband_type == 2) { // HL chroma - vertical chroma details (even less critical)
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return 1.3f;
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if (level >= 6) return 1.2f;
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if (level >= 5) return 1.4f;
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if (level >= 4) return 1.6f;
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if (level >= 3) return 1.8f;
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if (level >= 2) return 2.0f;
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return 2.2f;
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return FCLAMP(base * ANISOTROPY_MULT[enc->quality_level], 1.0f, 100.0f);
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} else { // HH chroma - diagonal chroma details (most aggressive)
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return 2.5f;
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if (level >= 6) return 1.4f;
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if (level >= 5) return 1.6f;
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if (level >= 4) return 1.8f;
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if (level >= 3) return 2.1f;
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if (level >= 2) return 2.3f;
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return 2.5f;
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return FCLAMP(base * ANISOTROPY_MULT[enc->quality_level] + ANISOTROPY_BIAS_CHROMA[enc->quality_level], 1.0f, 100.0f);
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}
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}
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}
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@@ -1009,28 +1000,12 @@ static void quantise_dwt_coefficients_perceptual_per_coeff(tav_encoder_t *enc,
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float effective_base_q = base_quantizer;
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effective_base_q = FCLAMP(effective_base_q, 1.0f, 255.0f);
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// Debug coefficient analysis
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if (frame_count == 1 || frame_count == 120) {
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int nonzero = 0;
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for (int i = 0; i < size; i++) {
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// Apply perceptual weight based on coefficient's position in DWT layout
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float weight = get_perceptual_weight_for_position(enc, i, width, height, decomp_levels, is_chroma);
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float effective_q = effective_base_q * weight;
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float quantised_val = coeffs[i] / effective_q;
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quantised[i] = (int16_t)CLAMP((int)(quantised_val + (quantised_val >= 0 ? 0.5f : -0.5f)), -32768, 32767);
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if (quantised[i] != 0) nonzero++;
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}
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printf("DEBUG: Frame 120 - %s channel: %d/%d nonzero coeffs after perceptual per-coeff quantization\n",
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is_chroma ? "Chroma" : "Luma", nonzero, size);
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} else {
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// Normal quantization loop
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for (int i = 0; i < size; i++) {
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// Apply perceptual weight based on coefficient's position in DWT layout
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float weight = get_perceptual_weight_for_position(enc, i, width, height, decomp_levels, is_chroma);
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float effective_q = effective_base_q * weight;
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float quantised_val = coeffs[i] / effective_q;
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quantised[i] = (int16_t)CLAMP((int)(quantised_val + (quantised_val >= 0 ? 0.5f : -0.5f)), -32768, 32767);
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}
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for (int i = 0; i < size; i++) {
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// Apply perceptual weight based on coefficient's position in DWT layout
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float weight = get_perceptual_weight_for_position(enc, i, width, height, decomp_levels, is_chroma);
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float effective_q = effective_base_q * weight;
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float quantised_val = coeffs[i] / effective_q;
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quantised[i] = (int16_t)CLAMP((int)(quantised_val + (quantised_val >= 0 ? 0.5f : -0.5f)), -32768, 32767);
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}
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}
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@@ -1373,7 +1348,7 @@ static size_t compress_and_write_frame(tav_encoder_t *enc, uint8_t packet_type)
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}*/
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// Debug: Check Y data before DWT transform
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if (enc->frame_count == 120 && enc->verbose) {
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/*if (enc->frame_count == 120 && enc->verbose) {
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float max_y_before = 0.0f;
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int nonzero_before = 0;
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int total_pixels = enc->monoblock ? (enc->width * enc->height) : (PADDED_TILE_SIZE_X * PADDED_TILE_SIZE_Y);
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@@ -1383,7 +1358,7 @@ static size_t compress_and_write_frame(tav_encoder_t *enc, uint8_t packet_type)
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if (abs_val > 0.1f) nonzero_before++;
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}
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printf("DEBUG: Y data before DWT: max=%.2f, nonzero=%d/%d\n", max_y_before, nonzero_before, total_pixels);
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}
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}*/
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// Apply DWT transform to each channel
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if (enc->monoblock) {
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@@ -1399,14 +1374,14 @@ static size_t compress_and_write_frame(tav_encoder_t *enc, uint8_t packet_type)
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}
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// Debug: Check Y data after DWT transform for high-frequency content
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if (enc->frame_count == 120 && enc->verbose) {
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/*if (enc->frame_count == 120 && enc->verbose) {
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printf("DEBUG: Y data after DWT (some high-freq samples): ");
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int sample_indices[] = {47034, 47035, 47036, 47037, 47038}; // HH1 start + some samples
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for (int i = 0; i < 5; i++) {
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printf("%.3f ", tile_y_data[sample_indices[i]]);
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}
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printf("\n");
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}
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}*/
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// Serialise tile
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size_t tile_size = serialise_tile_data(enc, tile_x, tile_y,
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