| /* |
| * Copyright (c) 2016, Alliance for Open Media. All rights reserved. |
| * |
| * This source code is subject to the terms of the BSD 2 Clause License and |
| * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License |
| * was not distributed with this source code in the LICENSE file, you can |
| * obtain it at www.aomedia.org/license/software. If the Alliance for Open |
| * Media Patent License 1.0 was not distributed with this source code in the |
| * PATENTS file, you can obtain it at www.aomedia.org/license/patent. |
| */ |
| |
| // Dense Inverse Search flow algorithm |
| // Paper: https://arxiv.org/abs/1603.03590 |
| |
| #include <assert.h> |
| #include <math.h> |
| |
| #include "aom_dsp/aom_dsp_common.h" |
| #include "aom_dsp/flow_estimation/corner_detect.h" |
| #include "aom_dsp/flow_estimation/disflow.h" |
| #include "aom_dsp/flow_estimation/ransac.h" |
| #include "aom_dsp/pyramid.h" |
| #include "aom_mem/aom_mem.h" |
| |
| #include "config/aom_dsp_rtcd.h" |
| |
| // Amount to downsample the flow field by. |
| // e.g., DOWNSAMPLE_SHIFT = 2 (DOWNSAMPLE_FACTOR == 4) means we calculate |
| // one flow point for each 4x4 pixel region of the frame |
| // Must be a power of 2 |
| #define DOWNSAMPLE_SHIFT 3 |
| #define DOWNSAMPLE_FACTOR (1 << DOWNSAMPLE_SHIFT) |
| |
| // Filters used when upscaling the flow field from one pyramid level |
| // to another. See upscale_flow_component for details on kernel selection |
| #define FLOW_UPSCALE_TAPS 4 |
| |
| // Number of outermost flow field entries (on each edge) which can't be |
| // computed, because the patch they correspond to extends outside of the |
| // frame |
| // The border is (DISFLOW_PATCH_SIZE >> 1) pixels, which is |
| // (DISFLOW_PATCH_SIZE >> 1) >> DOWNSAMPLE_SHIFT many flow field entries |
| #define FLOW_BORDER_INNER ((DISFLOW_PATCH_SIZE >> 1) >> DOWNSAMPLE_SHIFT) |
| |
| // Number of extra padding entries on each side of the flow field. |
| // These samples are added so that we do not need to apply clamping when |
| // interpolating or upsampling the flow field |
| #define FLOW_BORDER_OUTER (FLOW_UPSCALE_TAPS / 2) |
| |
| // When downsampling the flow field, each flow field entry covers a square |
| // region of pixels in the image pyramid. This value is equal to the position |
| // of the center of that region, as an offset from the top/left edge. |
| // |
| // Note: Using ((DOWNSAMPLE_FACTOR - 1) / 2) is equivalent to the more |
| // natural expression ((DOWNSAMPLE_FACTOR / 2) - 1), |
| // unless DOWNSAMPLE_FACTOR == 1 (ie, no downsampling), in which case |
| // this gives the correct offset of 0 instead of -1. |
| #define UPSAMPLE_CENTER_OFFSET ((DOWNSAMPLE_FACTOR - 1) / 2) |
| |
| static double flow_upscale_filter[2][FLOW_UPSCALE_TAPS] = { |
| // Cubic interpolation kernels for phase=0.75 and phase=0.25, respectively |
| { -3 / 128., 29 / 128., 111 / 128., -9 / 128. }, |
| { -9 / 128., 111 / 128., 29 / 128., -3 / 128. } |
| }; |
| |
| static inline void get_cubic_kernel_dbl(double x, double kernel[4]) { |
| // Check that the fractional position is in range. |
| // |
| // Note: x is calculated from, e.g., `u_frac = u - floor(u)`. |
| // Mathematically, this implies that 0 <= x < 1. However, in practice it is |
| // possible to have x == 1 due to floating point rounding. This is fine, |
| // and we still interpolate correctly if we allow x = 1. |
| assert(0 <= x && x <= 1); |
| |
| double x2 = x * x; |
| double x3 = x2 * x; |
| kernel[0] = -0.5 * x + x2 - 0.5 * x3; |
| kernel[1] = 1.0 - 2.5 * x2 + 1.5 * x3; |
| kernel[2] = 0.5 * x + 2.0 * x2 - 1.5 * x3; |
| kernel[3] = -0.5 * x2 + 0.5 * x3; |
| } |
| |
| static inline void get_cubic_kernel_int(double x, int kernel[4]) { |
| double kernel_dbl[4]; |
| get_cubic_kernel_dbl(x, kernel_dbl); |
| |
| kernel[0] = (int)rint(kernel_dbl[0] * (1 << DISFLOW_INTERP_BITS)); |
| kernel[1] = (int)rint(kernel_dbl[1] * (1 << DISFLOW_INTERP_BITS)); |
| kernel[2] = (int)rint(kernel_dbl[2] * (1 << DISFLOW_INTERP_BITS)); |
| kernel[3] = (int)rint(kernel_dbl[3] * (1 << DISFLOW_INTERP_BITS)); |
| } |
| |
| static inline double get_cubic_value_dbl(const double *p, |
| const double kernel[4]) { |
| return kernel[0] * p[0] + kernel[1] * p[1] + kernel[2] * p[2] + |
| kernel[3] * p[3]; |
| } |
| |
| static inline int get_cubic_value_int(const int *p, const int kernel[4]) { |
| return kernel[0] * p[0] + kernel[1] * p[1] + kernel[2] * p[2] + |
| kernel[3] * p[3]; |
| } |
| |
| static inline double bicubic_interp_one(const double *arr, int stride, |
| const double h_kernel[4], |
| const double v_kernel[4]) { |
| double tmp[1 * 4]; |
| |
| // Horizontal convolution |
| for (int i = -1; i < 3; ++i) { |
| tmp[i + 1] = get_cubic_value_dbl(&arr[i * stride - 1], h_kernel); |
| } |
| |
| // Vertical convolution |
| return get_cubic_value_dbl(tmp, v_kernel); |
| } |
| |
| static int determine_disflow_correspondence(const ImagePyramid *src_pyr, |
| const ImagePyramid *ref_pyr, |
| CornerList *corners, |
| const FlowField *flow, |
| Correspondence *correspondences) { |
| const int width = flow->width; |
| const int height = flow->height; |
| const int stride = flow->stride; |
| |
| int num_correspondences = 0; |
| for (int i = 0; i < corners->num_corners; ++i) { |
| const int x0 = corners->corners[2 * i]; |
| const int y0 = corners->corners[2 * i + 1]; |
| |
| // Offset points, to compensate for the fact that (say) a flow field entry |
| // at horizontal index i, is nominally associated with the pixel at |
| // horizontal coordinate (i << DOWNSAMPLE_FACTOR) + UPSAMPLE_CENTER_OFFSET |
| // This offset must be applied before we split the coordinate into integer |
| // and fractional parts, in order for the interpolation to be correct. |
| const int x = x0 - UPSAMPLE_CENTER_OFFSET; |
| const int y = y0 - UPSAMPLE_CENTER_OFFSET; |
| |
| // Split the pixel coordinates into integer flow field coordinates and |
| // an offset for interpolation |
| const int flow_x = x >> DOWNSAMPLE_SHIFT; |
| const double flow_sub_x = |
| (x & (DOWNSAMPLE_FACTOR - 1)) / (double)DOWNSAMPLE_FACTOR; |
| const int flow_y = y >> DOWNSAMPLE_SHIFT; |
| const double flow_sub_y = |
| (y & (DOWNSAMPLE_FACTOR - 1)) / (double)DOWNSAMPLE_FACTOR; |
| |
| // Exclude points which would sample from the outer border of the flow |
| // field, as this would give lower-quality results. |
| // |
| // Note: As we never read from the border region at pyramid level 0, we |
| // can skip filling it in. If the conditions here are removed, or any |
| // other logic is added which reads from this border region, then |
| // compute_flow_field() will need to be modified to call |
| // fill_flow_field_borders() at pyramid level 0 to set up the correct |
| // border data. |
| if (flow_x < 1 || (flow_x + 2) >= width) continue; |
| if (flow_y < 1 || (flow_y + 2) >= height) continue; |
| |
| double h_kernel[4]; |
| double v_kernel[4]; |
| get_cubic_kernel_dbl(flow_sub_x, h_kernel); |
| get_cubic_kernel_dbl(flow_sub_y, v_kernel); |
| |
| double flow_u = bicubic_interp_one(&flow->u[flow_y * stride + flow_x], |
| stride, h_kernel, v_kernel); |
| double flow_v = bicubic_interp_one(&flow->v[flow_y * stride + flow_x], |
| stride, h_kernel, v_kernel); |
| |
| // Refine the interpolated flow vector one last time |
| const int patch_tl_x = x0 - DISFLOW_PATCH_CENTER; |
| const int patch_tl_y = y0 - DISFLOW_PATCH_CENTER; |
| aom_compute_flow_at_point( |
| src_pyr->layers[0].buffer, ref_pyr->layers[0].buffer, patch_tl_x, |
| patch_tl_y, src_pyr->layers[0].width, src_pyr->layers[0].height, |
| src_pyr->layers[0].stride, &flow_u, &flow_v); |
| |
| // Use original points (without offsets) when filling in correspondence |
| // array |
| correspondences[num_correspondences].x = x0; |
| correspondences[num_correspondences].y = y0; |
| correspondences[num_correspondences].rx = x0 + flow_u; |
| correspondences[num_correspondences].ry = y0 + flow_v; |
| num_correspondences++; |
| } |
| return num_correspondences; |
| } |
| |
| // Compare two regions of width x height pixels, one rooted at position |
| // (x, y) in src and the other at (x + u, y + v) in ref. |
| // This function returns the sum of squared pixel differences between |
| // the two regions. |
| static inline void compute_flow_vector(const uint8_t *src, const uint8_t *ref, |
| int width, int height, int stride, int x, |
| int y, double u, double v, |
| const int16_t *dx, const int16_t *dy, |
| int *b) { |
| memset(b, 0, 2 * sizeof(*b)); |
| |
| // Split offset into integer and fractional parts, and compute cubic |
| // interpolation kernels |
| const int u_int = (int)floor(u); |
| const int v_int = (int)floor(v); |
| const double u_frac = u - floor(u); |
| const double v_frac = v - floor(v); |
| |
| int h_kernel[4]; |
| int v_kernel[4]; |
| get_cubic_kernel_int(u_frac, h_kernel); |
| get_cubic_kernel_int(v_frac, v_kernel); |
| |
| // Storage for intermediate values between the two convolution directions |
| int tmp_[DISFLOW_PATCH_SIZE * (DISFLOW_PATCH_SIZE + 3)]; |
| int *tmp = tmp_ + DISFLOW_PATCH_SIZE; // Offset by one row |
| |
| // Clamp coordinates so that all pixels we fetch will remain within the |
| // allocated border region, but allow them to go far enough out that |
| // the border pixels' values do not change. |
| // Since we are calculating an 8x8 block, the bottom-right pixel |
| // in the block has coordinates (x0 + 7, y0 + 7). Then, the cubic |
| // interpolation has 4 taps, meaning that the output of pixel |
| // (x_w, y_w) depends on the pixels in the range |
| // ([x_w - 1, x_w + 2], [y_w - 1, y_w + 2]). |
| // |
| // Thus the most extreme coordinates which will be fetched are |
| // (x0 - 1, y0 - 1) and (x0 + 9, y0 + 9). |
| const int x0 = clamp(x + u_int, -9, width); |
| const int y0 = clamp(y + v_int, -9, height); |
| |
| // Horizontal convolution |
| for (int i = -1; i < DISFLOW_PATCH_SIZE + 2; ++i) { |
| const int y_w = y0 + i; |
| for (int j = 0; j < DISFLOW_PATCH_SIZE; ++j) { |
| const int x_w = x0 + j; |
| int arr[4]; |
| |
| arr[0] = (int)ref[y_w * stride + (x_w - 1)]; |
| arr[1] = (int)ref[y_w * stride + (x_w + 0)]; |
| arr[2] = (int)ref[y_w * stride + (x_w + 1)]; |
| arr[3] = (int)ref[y_w * stride + (x_w + 2)]; |
| |
| // Apply kernel and round, keeping 6 extra bits of precision. |
| // |
| // 6 is the maximum allowable number of extra bits which will avoid |
| // the intermediate values overflowing an int16_t. The most extreme |
| // intermediate value occurs when: |
| // * The input pixels are [0, 255, 255, 0] |
| // * u_frac = 0.5 |
| // In this case, the un-scaled output is 255 * 1.125 = 286.875. |
| // As an integer with 6 fractional bits, that is 18360, which fits |
| // in an int16_t. But with 7 fractional bits it would be 36720, |
| // which is too large. |
| tmp[i * DISFLOW_PATCH_SIZE + j] = ROUND_POWER_OF_TWO( |
| get_cubic_value_int(arr, h_kernel), DISFLOW_INTERP_BITS - 6); |
| } |
| } |
| |
| // Vertical convolution |
| for (int i = 0; i < DISFLOW_PATCH_SIZE; ++i) { |
| for (int j = 0; j < DISFLOW_PATCH_SIZE; ++j) { |
| const int *p = &tmp[i * DISFLOW_PATCH_SIZE + j]; |
| const int arr[4] = { p[-DISFLOW_PATCH_SIZE], p[0], p[DISFLOW_PATCH_SIZE], |
| p[2 * DISFLOW_PATCH_SIZE] }; |
| const int result = get_cubic_value_int(arr, v_kernel); |
| |
| // Apply kernel and round. |
| // This time, we have to round off the 6 extra bits which were kept |
| // earlier, but we also want to keep DISFLOW_DERIV_SCALE_LOG2 extra bits |
| // of precision to match the scale of the dx and dy arrays. |
| const int round_bits = DISFLOW_INTERP_BITS + 6 - DISFLOW_DERIV_SCALE_LOG2; |
| const int warped = ROUND_POWER_OF_TWO(result, round_bits); |
| const int src_px = src[(x + j) + (y + i) * stride] << 3; |
| const int dt = warped - src_px; |
| b[0] += dx[i * DISFLOW_PATCH_SIZE + j] * dt; |
| b[1] += dy[i * DISFLOW_PATCH_SIZE + j] * dt; |
| } |
| } |
| } |
| |
| static inline void sobel_filter(const uint8_t *src, int src_stride, |
| int16_t *dst, int dst_stride, int dir) { |
| int16_t tmp_[DISFLOW_PATCH_SIZE * (DISFLOW_PATCH_SIZE + 2)]; |
| int16_t *tmp = tmp_ + DISFLOW_PATCH_SIZE; |
| |
| // Sobel filter kernel |
| // This must have an overall scale factor equal to DISFLOW_DERIV_SCALE, |
| // in order to produce correctly scaled outputs. |
| // To work out the scale factor, we multiply two factors: |
| // |
| // * For the derivative filter (sobel_a), comparing our filter |
| // image[x - 1] - image[x + 1] |
| // to the standard form |
| // d/dx image[x] = image[x+1] - image[x] |
| // tells us that we're actually calculating -2 * d/dx image[2] |
| // |
| // * For the smoothing filter (sobel_b), all coefficients are positive |
| // so the scale factor is just the sum of the coefficients |
| // |
| // Thus we need to make sure that DISFLOW_DERIV_SCALE = 2 * sum(sobel_b) |
| // (and take care of the - sign from sobel_a elsewhere) |
| static const int16_t sobel_a[3] = { 1, 0, -1 }; |
| static const int16_t sobel_b[3] = { 1, 2, 1 }; |
| const int taps = 3; |
| |
| // horizontal filter |
| const int16_t *h_kernel = dir ? sobel_a : sobel_b; |
| |
| for (int y = -1; y < DISFLOW_PATCH_SIZE + 1; ++y) { |
| for (int x = 0; x < DISFLOW_PATCH_SIZE; ++x) { |
| int sum = 0; |
| for (int k = 0; k < taps; ++k) { |
| sum += h_kernel[k] * src[y * src_stride + (x + k - 1)]; |
| } |
| tmp[y * DISFLOW_PATCH_SIZE + x] = sum; |
| } |
| } |
| |
| // vertical filter |
| const int16_t *v_kernel = dir ? sobel_b : sobel_a; |
| |
| for (int y = 0; y < DISFLOW_PATCH_SIZE; ++y) { |
| for (int x = 0; x < DISFLOW_PATCH_SIZE; ++x) { |
| int sum = 0; |
| for (int k = 0; k < taps; ++k) { |
| sum += v_kernel[k] * tmp[(y + k - 1) * DISFLOW_PATCH_SIZE + x]; |
| } |
| dst[y * dst_stride + x] = sum; |
| } |
| } |
| } |
| |
| // Computes the components of the system of equations used to solve for |
| // a flow vector. |
| // |
| // The flow equations are a least-squares system, derived as follows: |
| // |
| // For each pixel in the patch, we calculate the current error `dt`, |
| // and the x and y gradients `dx` and `dy` of the source patch. |
| // This means that, to first order, the squared error for this pixel is |
| // |
| // (dt + u * dx + v * dy)^2 |
| // |
| // where (u, v) are the incremental changes to the flow vector. |
| // |
| // We then want to find the values of u and v which minimize the sum |
| // of the squared error across all pixels. Conveniently, this fits exactly |
| // into the form of a least squares problem, with one equation |
| // |
| // u * dx + v * dy = -dt |
| // |
| // for each pixel. |
| // |
| // Summing across all pixels in a square window of size DISFLOW_PATCH_SIZE, |
| // and absorbing the - sign elsewhere, this results in the least squares system |
| // |
| // M = |sum(dx * dx) sum(dx * dy)| |
| // |sum(dx * dy) sum(dy * dy)| |
| // |
| // b = |sum(dx * dt)| |
| // |sum(dy * dt)| |
| static inline void compute_flow_matrix(const int16_t *dx, int dx_stride, |
| const int16_t *dy, int dy_stride, |
| double *M) { |
| int tmp[4] = { 0 }; |
| |
| for (int i = 0; i < DISFLOW_PATCH_SIZE; i++) { |
| for (int j = 0; j < DISFLOW_PATCH_SIZE; j++) { |
| tmp[0] += dx[i * dx_stride + j] * dx[i * dx_stride + j]; |
| tmp[1] += dx[i * dx_stride + j] * dy[i * dy_stride + j]; |
| // Don't compute tmp[2], as it should be equal to tmp[1] |
| tmp[3] += dy[i * dy_stride + j] * dy[i * dy_stride + j]; |
| } |
| } |
| |
| // Apply regularization |
| // We follow the standard regularization method of adding `k * I` before |
| // inverting. This ensures that the matrix will be invertible. |
| // |
| // Setting the regularization strength k to 1 seems to work well here, as |
| // typical values coming from the other equations are very large (1e5 to |
| // 1e6, with an upper limit of around 6e7, at the time of writing). |
| // It also preserves the property that all matrix values are whole numbers, |
| // which is convenient for integerized SIMD implementation. |
| tmp[0] += 1; |
| tmp[3] += 1; |
| |
| tmp[2] = tmp[1]; |
| |
| M[0] = (double)tmp[0]; |
| M[1] = (double)tmp[1]; |
| M[2] = (double)tmp[2]; |
| M[3] = (double)tmp[3]; |
| } |
| |
| // Try to invert the matrix M |
| // Note: Due to the nature of how a least-squares matrix is constructed, all of |
| // the eigenvalues will be >= 0, and therefore det M >= 0 as well. |
| // The regularization term `+ k * I` further ensures that det M >= k^2. |
| // As mentioned in compute_flow_matrix(), here we use k = 1, so det M >= 1. |
| // So we don't have to worry about non-invertible matrices here. |
| static inline void invert_2x2(const double *M, double *M_inv) { |
| double det = (M[0] * M[3]) - (M[1] * M[2]); |
| assert(det >= 1); |
| const double det_inv = 1 / det; |
| |
| M_inv[0] = M[3] * det_inv; |
| M_inv[1] = -M[1] * det_inv; |
| M_inv[2] = -M[2] * det_inv; |
| M_inv[3] = M[0] * det_inv; |
| } |
| |
| void aom_compute_flow_at_point_c(const uint8_t *src, const uint8_t *ref, int x, |
| int y, int width, int height, int stride, |
| double *u, double *v) { |
| double M[4]; |
| double M_inv[4]; |
| int b[2]; |
| int16_t dx[DISFLOW_PATCH_SIZE * DISFLOW_PATCH_SIZE]; |
| int16_t dy[DISFLOW_PATCH_SIZE * DISFLOW_PATCH_SIZE]; |
| |
| // Compute gradients within this patch |
| const uint8_t *src_patch = &src[y * stride + x]; |
| sobel_filter(src_patch, stride, dx, DISFLOW_PATCH_SIZE, 1); |
| sobel_filter(src_patch, stride, dy, DISFLOW_PATCH_SIZE, 0); |
| |
| compute_flow_matrix(dx, DISFLOW_PATCH_SIZE, dy, DISFLOW_PATCH_SIZE, M); |
| invert_2x2(M, M_inv); |
| |
| for (int itr = 0; itr < DISFLOW_MAX_ITR; itr++) { |
| compute_flow_vector(src, ref, width, height, stride, x, y, *u, *v, dx, dy, |
| b); |
| |
| // Solve flow equations to find a better estimate for the flow vector |
| // at this point |
| const double step_u = M_inv[0] * b[0] + M_inv[1] * b[1]; |
| const double step_v = M_inv[2] * b[0] + M_inv[3] * b[1]; |
| *u += fclamp(step_u * DISFLOW_STEP_SIZE, -2, 2); |
| *v += fclamp(step_v * DISFLOW_STEP_SIZE, -2, 2); |
| |
| if (fabs(step_u) + fabs(step_v) < DISFLOW_STEP_SIZE_THRESOLD) { |
| // Stop iteration when we're close to convergence |
| break; |
| } |
| } |
| } |
| |
| static void fill_flow_field_borders(double *flow, int width, int height, |
| int stride) { |
| // Calculate the bounds of the rectangle which was filled in by |
| // compute_flow_field() before calling this function. |
| // These indices are inclusive on both ends. |
| const int left_index = FLOW_BORDER_INNER; |
| const int right_index = (width - FLOW_BORDER_INNER - 1); |
| const int top_index = FLOW_BORDER_INNER; |
| const int bottom_index = (height - FLOW_BORDER_INNER - 1); |
| |
| // Left area |
| for (int i = top_index; i <= bottom_index; i += 1) { |
| double *row = flow + i * stride; |
| const double left = row[left_index]; |
| for (int j = -FLOW_BORDER_OUTER; j < left_index; j++) { |
| row[j] = left; |
| } |
| } |
| |
| // Right area |
| for (int i = top_index; i <= bottom_index; i += 1) { |
| double *row = flow + i * stride; |
| const double right = row[right_index]; |
| for (int j = right_index + 1; j < width + FLOW_BORDER_OUTER; j++) { |
| row[j] = right; |
| } |
| } |
| |
| // Top area |
| const double *top_row = flow + top_index * stride - FLOW_BORDER_OUTER; |
| for (int i = -FLOW_BORDER_OUTER; i < top_index; i++) { |
| double *row = flow + i * stride - FLOW_BORDER_OUTER; |
| size_t length = width + 2 * FLOW_BORDER_OUTER; |
| memcpy(row, top_row, length * sizeof(*row)); |
| } |
| |
| // Bottom area |
| const double *bottom_row = flow + bottom_index * stride - FLOW_BORDER_OUTER; |
| for (int i = bottom_index + 1; i < height + FLOW_BORDER_OUTER; i++) { |
| double *row = flow + i * stride - FLOW_BORDER_OUTER; |
| size_t length = width + 2 * FLOW_BORDER_OUTER; |
| memcpy(row, bottom_row, length * sizeof(*row)); |
| } |
| } |
| |
| // Upscale one component of the flow field, from a size of |
| // cur_width x cur_height to a size of (2*cur_width) x (2*cur_height), storing |
| // the result back into the same buffer. This function also scales the flow |
| // vector by 2, so that when we move to the next pyramid level down, the implied |
| // motion vector is the same. |
| // |
| // The temporary buffer tmpbuf must be large enough to hold an intermediate |
| // array of size stride * cur_height, *plus* FLOW_BORDER_OUTER rows above and |
| // below. In other words, indices from -FLOW_BORDER_OUTER * stride to |
| // (cur_height + FLOW_BORDER_OUTER) * stride - 1 must be valid. |
| // |
| // Note that the same stride is used for u before and after upscaling |
| // and for the temporary buffer, for simplicity. |
| // |
| // A note on phasing: |
| // |
| // The flow fields at two adjacent pyramid levels are offset from each other, |
| // and we need to account for this in the construction of the interpolation |
| // kernels. |
| // |
| // Consider an 8x8 pixel patch at pyramid level n. This is split into four |
| // patches at pyramid level n-1. Bringing these patches back up to pyramid level |
| // n, each sub-patch covers 4x4 pixels, and between them they cover the same |
| // 8x8 region. |
| // |
| // Therefore, at pyramid level n, two adjacent patches look like this: |
| // |
| // + - - - - - - - + - - - - - - - + |
| // | | | |
| // | x x | x x | |
| // | | | |
| // | # | # | |
| // | | | |
| // | x x | x x | |
| // | | | |
| // + - - - - - - - + - - - - - - - + |
| // |
| // where # marks the center of a patch at pyramid level n (the input to this |
| // function), and x marks the center of a patch at pyramid level n-1 (the output |
| // of this function). |
| // |
| // By counting pixels (marked by +, -, and |), we can see that the flow vectors |
| // at pyramid level n-1 are offset relative to the flow vectors at pyramid |
| // level n, by 1/4 of the larger (input) patch size. Therefore, our |
| // interpolation kernels need to have phases of 0.25 and 0.75. |
| // |
| // In addition, in order to handle the frame edges correctly, we need to |
| // generate one output vector to the left and one to the right of each input |
| // vector, even though these must be interpolated using different source points. |
| static void upscale_flow_component(double *flow, int cur_width, int cur_height, |
| int stride, double *tmpbuf) { |
| const int half_len = FLOW_UPSCALE_TAPS / 2; |
| |
| // Check that the outer border is large enough to avoid needing to clamp |
| // the source locations |
| assert(half_len <= FLOW_BORDER_OUTER); |
| |
| // Horizontal upscale and multiply by 2 |
| for (int i = 0; i < cur_height; i++) { |
| for (int j = 0; j < cur_width; j++) { |
| double left = 0; |
| for (int k = -half_len; k < half_len; k++) { |
| left += |
| flow[i * stride + (j + k)] * flow_upscale_filter[0][k + half_len]; |
| } |
| tmpbuf[i * stride + (2 * j + 0)] = 2.0 * left; |
| |
| // Right output pixel is 0.25 units to the right of the input pixel |
| double right = 0; |
| for (int k = -(half_len - 1); k < (half_len + 1); k++) { |
| right += flow[i * stride + (j + k)] * |
| flow_upscale_filter[1][k + (half_len - 1)]; |
| } |
| tmpbuf[i * stride + (2 * j + 1)] = 2.0 * right; |
| } |
| } |
| |
| // Fill in top and bottom borders of tmpbuf |
| const double *top_row = &tmpbuf[0]; |
| for (int i = -FLOW_BORDER_OUTER; i < 0; i++) { |
| double *row = &tmpbuf[i * stride]; |
| memcpy(row, top_row, 2 * cur_width * sizeof(*row)); |
| } |
| |
| const double *bottom_row = &tmpbuf[(cur_height - 1) * stride]; |
| for (int i = cur_height; i < cur_height + FLOW_BORDER_OUTER; i++) { |
| double *row = &tmpbuf[i * stride]; |
| memcpy(row, bottom_row, 2 * cur_width * sizeof(*row)); |
| } |
| |
| // Vertical upscale |
| int upscaled_width = cur_width * 2; |
| for (int i = 0; i < cur_height; i++) { |
| for (int j = 0; j < upscaled_width; j++) { |
| double top = 0; |
| for (int k = -half_len; k < half_len; k++) { |
| top += |
| tmpbuf[(i + k) * stride + j] * flow_upscale_filter[0][k + half_len]; |
| } |
| flow[(2 * i) * stride + j] = top; |
| |
| double bottom = 0; |
| for (int k = -(half_len - 1); k < (half_len + 1); k++) { |
| bottom += tmpbuf[(i + k) * stride + j] * |
| flow_upscale_filter[1][k + (half_len - 1)]; |
| } |
| flow[(2 * i + 1) * stride + j] = bottom; |
| } |
| } |
| } |
| |
| // make sure flow_u and flow_v start at 0 |
| static bool compute_flow_field(const ImagePyramid *src_pyr, |
| const ImagePyramid *ref_pyr, int n_levels, |
| FlowField *flow) { |
| bool mem_status = true; |
| |
| double *flow_u = flow->u; |
| double *flow_v = flow->v; |
| |
| double *tmpbuf0; |
| double *tmpbuf; |
| |
| if (n_levels < 2) { |
| // tmpbuf not needed |
| tmpbuf0 = NULL; |
| tmpbuf = NULL; |
| } else { |
| // This line must match the calculation of cur_flow_height below |
| const int layer1_height = src_pyr->layers[1].height >> DOWNSAMPLE_SHIFT; |
| |
| const size_t tmpbuf_size = |
| (layer1_height + 2 * FLOW_BORDER_OUTER) * flow->stride; |
| tmpbuf0 = aom_malloc(tmpbuf_size * sizeof(*tmpbuf0)); |
| if (!tmpbuf0) { |
| mem_status = false; |
| goto free_tmpbuf; |
| } |
| tmpbuf = tmpbuf0 + FLOW_BORDER_OUTER * flow->stride; |
| } |
| |
| // Compute flow field from coarsest to finest level of the pyramid |
| // |
| // Note: We stop after refining pyramid level 1 and interpolating it to |
| // generate an initial flow field at level 0. We do *not* refine the dense |
| // flow field at level 0. Instead, we wait until we have generated |
| // correspondences by interpolating this flow field, and then refine the |
| // correspondences themselves. This is both faster and gives better output |
| // compared to refining the flow field at level 0 and then interpolating. |
| for (int level = n_levels - 1; level >= 1; --level) { |
| const PyramidLayer *cur_layer = &src_pyr->layers[level]; |
| const int cur_width = cur_layer->width; |
| const int cur_height = cur_layer->height; |
| const int cur_stride = cur_layer->stride; |
| |
| const uint8_t *src_buffer = cur_layer->buffer; |
| const uint8_t *ref_buffer = ref_pyr->layers[level].buffer; |
| |
| const int cur_flow_width = cur_width >> DOWNSAMPLE_SHIFT; |
| const int cur_flow_height = cur_height >> DOWNSAMPLE_SHIFT; |
| const int cur_flow_stride = flow->stride; |
| |
| for (int i = FLOW_BORDER_INNER; i < cur_flow_height - FLOW_BORDER_INNER; |
| i += 1) { |
| for (int j = FLOW_BORDER_INNER; j < cur_flow_width - FLOW_BORDER_INNER; |
| j += 1) { |
| const int flow_field_idx = i * cur_flow_stride + j; |
| |
| // Calculate the position of a patch of size DISFLOW_PATCH_SIZE pixels, |
| // which is centered on the region covered by this flow field entry |
| const int patch_center_x = |
| (j << DOWNSAMPLE_SHIFT) + UPSAMPLE_CENTER_OFFSET; // In pixels |
| const int patch_center_y = |
| (i << DOWNSAMPLE_SHIFT) + UPSAMPLE_CENTER_OFFSET; // In pixels |
| const int patch_tl_x = patch_center_x - DISFLOW_PATCH_CENTER; |
| const int patch_tl_y = patch_center_y - DISFLOW_PATCH_CENTER; |
| assert(patch_tl_x >= 0); |
| assert(patch_tl_y >= 0); |
| |
| aom_compute_flow_at_point(src_buffer, ref_buffer, patch_tl_x, |
| patch_tl_y, cur_width, cur_height, cur_stride, |
| &flow_u[flow_field_idx], |
| &flow_v[flow_field_idx]); |
| } |
| } |
| |
| // Fill in the areas which we haven't explicitly computed, with copies |
| // of the outermost values which we did compute |
| fill_flow_field_borders(flow_u, cur_flow_width, cur_flow_height, |
| cur_flow_stride); |
| fill_flow_field_borders(flow_v, cur_flow_width, cur_flow_height, |
| cur_flow_stride); |
| |
| if (level > 0) { |
| const int upscale_flow_width = cur_flow_width << 1; |
| const int upscale_flow_height = cur_flow_height << 1; |
| const int upscale_stride = flow->stride; |
| |
| upscale_flow_component(flow_u, cur_flow_width, cur_flow_height, |
| cur_flow_stride, tmpbuf); |
| upscale_flow_component(flow_v, cur_flow_width, cur_flow_height, |
| cur_flow_stride, tmpbuf); |
| |
| // If we didn't fill in the rightmost column or bottommost row during |
| // upsampling (in order to keep the ratio to exactly 2), fill them |
| // in here by copying the next closest column/row |
| const PyramidLayer *next_layer = &src_pyr->layers[level - 1]; |
| const int next_flow_width = next_layer->width >> DOWNSAMPLE_SHIFT; |
| const int next_flow_height = next_layer->height >> DOWNSAMPLE_SHIFT; |
| |
| // Rightmost column |
| if (next_flow_width > upscale_flow_width) { |
| assert(next_flow_width == upscale_flow_width + 1); |
| for (int i = 0; i < upscale_flow_height; i++) { |
| const int index = i * upscale_stride + upscale_flow_width; |
| flow_u[index] = flow_u[index - 1]; |
| flow_v[index] = flow_v[index - 1]; |
| } |
| } |
| |
| // Bottommost row |
| if (next_flow_height > upscale_flow_height) { |
| assert(next_flow_height == upscale_flow_height + 1); |
| for (int j = 0; j < next_flow_width; j++) { |
| const int index = upscale_flow_height * upscale_stride + j; |
| flow_u[index] = flow_u[index - upscale_stride]; |
| flow_v[index] = flow_v[index - upscale_stride]; |
| } |
| } |
| } |
| } |
| |
| free_tmpbuf: |
| aom_free(tmpbuf0); |
| return mem_status; |
| } |
| |
| static FlowField *alloc_flow_field(int frame_width, int frame_height) { |
| FlowField *flow = (FlowField *)aom_malloc(sizeof(FlowField)); |
| if (flow == NULL) return NULL; |
| |
| // Calculate the size of the bottom (largest) layer of the flow pyramid |
| flow->width = frame_width >> DOWNSAMPLE_SHIFT; |
| flow->height = frame_height >> DOWNSAMPLE_SHIFT; |
| flow->stride = flow->width + 2 * FLOW_BORDER_OUTER; |
| |
| const size_t flow_size = |
| flow->stride * (size_t)(flow->height + 2 * FLOW_BORDER_OUTER); |
| |
| flow->buf0 = aom_calloc(2 * flow_size, sizeof(*flow->buf0)); |
| if (!flow->buf0) { |
| aom_free(flow); |
| return NULL; |
| } |
| |
| flow->u = flow->buf0 + FLOW_BORDER_OUTER * flow->stride + FLOW_BORDER_OUTER; |
| flow->v = flow->u + flow_size; |
| |
| return flow; |
| } |
| |
| static void free_flow_field(FlowField *flow) { |
| aom_free(flow->buf0); |
| aom_free(flow); |
| } |
| |
| // Compute flow field between `src` and `ref`, and then use that flow to |
| // compute a global motion model relating the two frames. |
| // |
| // Following the convention in flow_estimation.h, the flow vectors are computed |
| // at fixed points in `src` and point to the corresponding locations in `ref`, |
| // regardless of the temporal ordering of the frames. |
| bool av1_compute_global_motion_disflow( |
| TransformationType type, YV12_BUFFER_CONFIG *src, YV12_BUFFER_CONFIG *ref, |
| int bit_depth, int downsample_level, MotionModel *motion_models, |
| int num_motion_models, bool *mem_alloc_failed) { |
| // Precompute information we will need about each frame |
| ImagePyramid *src_pyramid = src->y_pyramid; |
| CornerList *src_corners = src->corners; |
| ImagePyramid *ref_pyramid = ref->y_pyramid; |
| |
| const int src_layers = |
| aom_compute_pyramid(src, bit_depth, DISFLOW_PYRAMID_LEVELS, src_pyramid); |
| const int ref_layers = |
| aom_compute_pyramid(ref, bit_depth, DISFLOW_PYRAMID_LEVELS, ref_pyramid); |
| |
| if (src_layers < 0 || ref_layers < 0) { |
| *mem_alloc_failed = true; |
| return false; |
| } |
| if (!av1_compute_corner_list(src, bit_depth, downsample_level, src_corners)) { |
| *mem_alloc_failed = true; |
| return false; |
| } |
| |
| assert(src_layers == ref_layers); |
| |
| const int src_width = src_pyramid->layers[0].width; |
| const int src_height = src_pyramid->layers[0].height; |
| assert(ref_pyramid->layers[0].width == src_width); |
| assert(ref_pyramid->layers[0].height == src_height); |
| |
| FlowField *flow = alloc_flow_field(src_width, src_height); |
| if (!flow) { |
| *mem_alloc_failed = true; |
| return false; |
| } |
| |
| if (!compute_flow_field(src_pyramid, ref_pyramid, src_layers, flow)) { |
| *mem_alloc_failed = true; |
| free_flow_field(flow); |
| return false; |
| } |
| |
| // find correspondences between the two images using the flow field |
| Correspondence *correspondences = |
| aom_malloc(src_corners->num_corners * sizeof(*correspondences)); |
| if (!correspondences) { |
| *mem_alloc_failed = true; |
| free_flow_field(flow); |
| return false; |
| } |
| |
| const int num_correspondences = determine_disflow_correspondence( |
| src_pyramid, ref_pyramid, src_corners, flow, correspondences); |
| |
| bool result = ransac(correspondences, num_correspondences, type, |
| motion_models, num_motion_models, mem_alloc_failed); |
| |
| aom_free(correspondences); |
| free_flow_field(flow); |
| return result; |
| } |