// Created by Claude on 2025-10-17 // OpenCV-based optical flow and mesh warping functions for TAV encoder // This file is compiled separately as C++ and linked with the C encoder #include #include #include #include #include // Extern "C" linkage for functions callable from C code extern "C" { // Helper: Compute SAD (Sum of Absolute Differences) for a block static int compute_sad( const unsigned char *ref, const unsigned char *cur, int ref_x, int ref_y, int cur_x, int cur_y, int width, int height, int block_size ) { int sad = 0; for (int by = 0; by < block_size; by++) { for (int bx = 0; bx < block_size; bx++) { int ry = ref_y + by; int rx = ref_x + bx; int cy = cur_y + by; int cx = cur_x + bx; // Boundary check if (rx < 0 || rx >= width || ry < 0 || ry >= height || cx < 0 || cx >= width || cy < 0 || cy >= height) { sad += 255; // Penalty for out-of-bounds continue; } int ref_val = ref[ry * width + rx]; int cur_val = cur[cy * width + cx]; sad += abs(ref_val - cur_val); } } return sad; } // Helper: Diamond search pattern for motion estimation static void diamond_search( const unsigned char *ref, const unsigned char *cur, int cx, int cy, int width, int height, int block_size, int search_range, int *best_dx, int *best_dy ) { // Large diamond pattern (distance 2) const int large_diamond[8][2] = { {0, -2}, {-1, -1}, {1, -1}, {-2, 0}, {2, 0}, {-1, 1}, {1, 1}, {0, 2} }; // Small diamond pattern (distance 1) const int small_diamond[4][2] = { {0, -1}, {-1, 0}, {1, 0}, {0, 1} }; int dx = 0, dy = 0; int best_sad = compute_sad(ref, cur, cx + dx, cy + dy, cx, cy, width, height, block_size); // Large diamond search bool improved = true; while (improved) { improved = false; for (int i = 0; i < 8; i++) { int test_dx = dx + large_diamond[i][0]; int test_dy = dy + large_diamond[i][1]; // Check search range bounds if (abs(test_dx) > search_range || abs(test_dy) > search_range) { continue; } int sad = compute_sad(ref, cur, cx + test_dx, cy + test_dy, cx, cy, width, height, block_size); if (sad < best_sad) { best_sad = sad; dx = test_dx; dy = test_dy; improved = true; break; } } } // Small diamond refinement improved = true; while (improved) { improved = false; for (int i = 0; i < 4; i++) { int test_dx = dx + small_diamond[i][0]; int test_dy = dy + small_diamond[i][1]; if (abs(test_dx) > search_range || abs(test_dy) > search_range) { continue; } int sad = compute_sad(ref, cur, cx + test_dx, cy + test_dy, cx, cy, width, height, block_size); if (sad < best_sad) { best_sad = sad; dx = test_dx; dy = test_dy; improved = true; break; } } } *best_dx = dx; *best_dy = dy; } // Hierarchical block matching motion estimation with deeper pyramid // 3-level hierarchy to handle large motion (up to ±32px) void estimate_motion_optical_flow( const unsigned char *frame1_rgb, const unsigned char *frame2_rgb, int width, int height, float **out_flow_x, float **out_flow_y ) { // Step 1: Convert RGB to grayscale unsigned char *gray1 = (unsigned char*)std::malloc(width * height); unsigned char *gray2 = (unsigned char*)std::malloc(width * height); for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { int idx = y * width + x; int rgb_idx = idx * 3; // ITU-R BT.601 grayscale conversion gray1[idx] = (unsigned char)(0.299f * frame1_rgb[rgb_idx] + 0.587f * frame1_rgb[rgb_idx + 1] + 0.114f * frame1_rgb[rgb_idx + 2]); gray2[idx] = (unsigned char)(0.299f * frame2_rgb[rgb_idx] + 0.587f * frame2_rgb[rgb_idx + 1] + 0.114f * frame2_rgb[rgb_idx + 2]); } } // Step 2: 3-level hierarchical block matching (coarse to fine) // Level 0: 64×64 blocks, ±32 pixel search (captures large motion up to 32px) // Level 1: 32×32 blocks, ±16 pixel refinement // Level 2: 16×16 blocks, ±8 pixel final refinement *out_flow_x = (float*)std::malloc(width * height * sizeof(float)); *out_flow_y = (float*)std::malloc(width * height * sizeof(float)); // Initialize with zero motion std::memset(*out_flow_x, 0, width * height * sizeof(float)); std::memset(*out_flow_y, 0, width * height * sizeof(float)); // Level 0: Coarsest search (64×64 blocks, ±32px) const int block_size_l0 = 32; const int search_range_l0 = 16; for (int by = 0; by < height; by += block_size_l0) { for (int bx = 0; bx < width; bx += block_size_l0) { int dx = 0, dy = 0; diamond_search(gray1, gray2, bx, by, width, height, block_size_l0, search_range_l0, &dx, &dy); // Fill flow for this block for (int y = by; y < by + block_size_l0 && y < height; y++) { for (int x = bx; x < bx + block_size_l0 && x < width; x++) { int idx = y * width + x; (*out_flow_x)[idx] = (float)dx; (*out_flow_y)[idx] = (float)dy; } } } } // Level 1: Medium refinement (32×32 blocks, ±16px) const int block_size_l1 = 16; const int search_range_l1 = 8; for (int by = 0; by < height; by += block_size_l1) { for (int bx = 0; bx < width; bx += block_size_l1) { // Get initial guess from level 0 int init_dx = (int)(*out_flow_x)[by * width + bx]; int init_dy = (int)(*out_flow_y)[by * width + bx]; // Search around initial guess int best_dx = init_dx; int best_dy = init_dy; int best_sad = compute_sad(gray1, gray2, bx + init_dx, by + init_dy, bx, by, width, height, block_size_l1); // Local search around initial guess for (int dy = -search_range_l1; dy <= search_range_l1; dy += 2) { for (int dx = -search_range_l1; dx <= search_range_l1; dx += 2) { int test_dx = init_dx + dx; int test_dy = init_dy + dy; int sad = compute_sad(gray1, gray2, bx + test_dx, by + test_dy, bx, by, width, height, block_size_l1); if (sad < best_sad) { best_sad = sad; best_dx = test_dx; best_dy = test_dy; } } } // Fill flow for this block for (int y = by; y < by + block_size_l1 && y < height; y++) { for (int x = bx; x < bx + block_size_l1 && x < width; x++) { int idx = y * width + x; (*out_flow_x)[idx] = (float)best_dx; (*out_flow_y)[idx] = (float)best_dy; } } } } // Level 2: Finest refinement (16×16 blocks, ±8px) /*const int block_size_l2 = 16; const int search_range_l2 = 8; for (int by = 0; by < height; by += block_size_l2) { for (int bx = 0; bx < width; bx += block_size_l2) { // Get initial guess from level 1 int init_dx = (int)(*out_flow_x)[by * width + bx]; int init_dy = (int)(*out_flow_y)[by * width + bx]; // Search around initial guess (finer grid) int best_dx = init_dx; int best_dy = init_dy; int best_sad = compute_sad(gray1, gray2, bx + init_dx, by + init_dy, bx, by, width, height, block_size_l2); // Exhaustive local search for final refinement for (int dy = -search_range_l2; dy <= search_range_l2; dy++) { for (int dx = -search_range_l2; dx <= search_range_l2; dx++) { int test_dx = init_dx + dx; int test_dy = init_dy + dy; int sad = compute_sad(gray1, gray2, bx + test_dx, by + test_dy, bx, by, width, height, block_size_l2); if (sad < best_sad) { best_sad = sad; best_dx = test_dx; best_dy = test_dy; } } } // Fill flow for this block for (int y = by; y < by + block_size_l2 && y < height; y++) { for (int x = bx; x < bx + block_size_l2 && x < width; x++) { int idx = y * width + x; (*out_flow_x)[idx] = (float)best_dx; (*out_flow_y)[idx] = (float)best_dy; } } } }*/ std::free(gray1); std::free(gray2); } // Build distortion mesh from dense optical flow field // Downsamples flow to coarse mesh grid using robust averaging void build_mesh_from_flow( const float *flow_x, const float *flow_y, int width, int height, int mesh_w, int mesh_h, short *mesh_dx, short *mesh_dy // Output: 1/8 pixel precision ) { int cell_w = width / mesh_w; int cell_h = height / mesh_h; for (int my = 0; my < mesh_h; my++) { for (int mx = 0; mx < mesh_w; mx++) { // Cell center coordinates (control point position) int cx = mx * cell_w + cell_w / 2; int cy = my * cell_h + cell_h / 2; // Collect flow vectors in a neighborhood around cell center (5×5 window) float sum_dx = 0.0f, sum_dy = 0.0f; int count = 0; for (int dy = -2; dy <= 2; dy++) { for (int dx = -2; dx <= 2; dx++) { int px = cx + dx; int py = cy + dy; if (px >= 0 && px < width && py >= 0 && py < height) { int idx = py * width + px; sum_dx += flow_x[idx]; sum_dy += flow_y[idx]; count++; } } } // Average and convert to 1/8 pixel precision float avg_dx = (count > 0) ? (sum_dx / count) : 0.0f; float avg_dy = (count > 0) ? (sum_dy / count) : 0.0f; int mesh_idx = my * mesh_w + mx; mesh_dx[mesh_idx] = (short)(avg_dx * 8.0f); // 1/8 pixel precision mesh_dy[mesh_idx] = (short)(avg_dy * 8.0f); } } } // Apply Laplacian smoothing to mesh for spatial coherence // This prevents fold-overs and reduces high-frequency noise void smooth_mesh_laplacian( short *mesh_dx, short *mesh_dy, int mesh_width, int mesh_height, float smoothness, int iterations ) { short *temp_dx = (short*)std::malloc(mesh_width * mesh_height * sizeof(short)); short *temp_dy = (short*)std::malloc(mesh_width * mesh_height * sizeof(short)); for (int iter = 0; iter < iterations; iter++) { std::memcpy(temp_dx, mesh_dx, mesh_width * mesh_height * sizeof(short)); std::memcpy(temp_dy, mesh_dy, mesh_width * mesh_height * sizeof(short)); for (int my = 0; my < mesh_height; my++) { for (int mx = 0; mx < mesh_width; mx++) { int idx = my * mesh_width + mx; // Collect neighbor displacements float neighbor_dx = 0.0f, neighbor_dy = 0.0f; int neighbor_count = 0; // 4-connected neighbors (up, down, left, right) int neighbors[4][2] = {{0, -1}, {0, 1}, {-1, 0}, {1, 0}}; for (int n = 0; n < 4; n++) { int nx = mx + neighbors[n][0]; int ny = my + neighbors[n][1]; if (nx >= 0 && nx < mesh_width && ny >= 0 && ny < mesh_height) { int nidx = ny * mesh_width + nx; neighbor_dx += temp_dx[nidx]; neighbor_dy += temp_dy[nidx]; neighbor_count++; } } if (neighbor_count > 0) { neighbor_dx /= neighbor_count; neighbor_dy /= neighbor_count; // Weighted average: data term + smoothness term float data_weight = 1.0f - smoothness; mesh_dx[idx] = (short)(data_weight * temp_dx[idx] + smoothness * neighbor_dx); mesh_dy[idx] = (short)(data_weight * temp_dy[idx] + smoothness * neighbor_dy); } } } } std::free(temp_dx); std::free(temp_dy); } // Apply bilinear mesh warp to a frame channel // Uses inverse mapping (destination → source) to avoid holes void warp_frame_with_mesh( const float *src_frame, int width, int height, const short *mesh_dx, const short *mesh_dy, int mesh_width, int mesh_height, float *dst_frame ) { int cell_w = width / mesh_width; int cell_h = height / mesh_height; // For each output pixel, compute source location using mesh warp for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { // Find which mesh cell this pixel belongs to int cell_x = x / cell_w; int cell_y = y / cell_h; // Clamp to valid mesh range if (cell_x >= mesh_width - 1) cell_x = mesh_width - 2; if (cell_y >= mesh_height - 1) cell_y = mesh_height - 2; if (cell_x < 0) cell_x = 0; if (cell_y < 0) cell_y = 0; // Get four corner control points int idx_00 = cell_y * mesh_width + cell_x; int idx_10 = idx_00 + 1; int idx_01 = (cell_y + 1) * mesh_width + cell_x; int idx_11 = idx_01 + 1; // Control point positions (cell centers) float cp_x0 = cell_x * cell_w + cell_w / 2.0f; float cp_y0 = cell_y * cell_h + cell_h / 2.0f; float cp_x1 = (cell_x + 1) * cell_w + cell_w / 2.0f; float cp_y1 = (cell_y + 1) * cell_h + cell_h / 2.0f; // Local coordinates within cell (0 to 1) float alpha = (x - cp_x0) / (cp_x1 - cp_x0); float beta = (y - cp_y0) / (cp_y1 - cp_y0); if (alpha < 0.0f) alpha = 0.0f; if (alpha > 1.0f) alpha = 1.0f; if (beta < 0.0f) beta = 0.0f; if (beta > 1.0f) beta = 1.0f; // Bilinear interpolation of motion vectors float dx_00 = mesh_dx[idx_00] / 8.0f; // Convert to pixels float dy_00 = mesh_dy[idx_00] / 8.0f; float dx_10 = mesh_dx[idx_10] / 8.0f; float dy_10 = mesh_dy[idx_10] / 8.0f; float dx_01 = mesh_dx[idx_01] / 8.0f; float dy_01 = mesh_dy[idx_01] / 8.0f; float dx_11 = mesh_dx[idx_11] / 8.0f; float dy_11 = mesh_dy[idx_11] / 8.0f; float dx = (1 - alpha) * (1 - beta) * dx_00 + alpha * (1 - beta) * dx_10 + (1 - alpha) * beta * dx_01 + alpha * beta * dx_11; float dy = (1 - alpha) * (1 - beta) * dy_00 + alpha * (1 - beta) * dy_10 + (1 - alpha) * beta * dy_01 + alpha * beta * dy_11; // Source coordinates (inverse warp: dst → src) float src_x = x + dx; float src_y = y + dy; // Bilinear interpolation of source pixel int sx0 = (int)std::floor(src_x); int sy0 = (int)std::floor(src_y); int sx1 = sx0 + 1; int sy1 = sy0 + 1; // Clamp to frame bounds if (sx0 < 0) sx0 = 0; if (sy0 < 0) sy0 = 0; if (sx1 >= width) sx1 = width - 1; if (sy1 >= height) sy1 = height - 1; if (sx0 >= width) sx0 = width - 1; if (sy0 >= height) sy0 = height - 1; float fx = src_x - sx0; float fy = src_y - sy0; // Bilinear interpolation float val_00 = src_frame[sy0 * width + sx0]; float val_10 = src_frame[sy0 * width + sx1]; float val_01 = src_frame[sy1 * width + sx0]; float val_11 = src_frame[sy1 * width + sx1]; float val = (1 - fx) * (1 - fy) * val_00 + fx * (1 - fy) * val_10 + (1 - fx) * fy * val_01 + fx * fy * val_11; dst_frame[y * width + x] = val; } } } } // extern "C"