| /* |
| * 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. |
| */ |
| #ifdef HAVE_CONFIG_H |
| #include "config.h" |
| #endif |
| |
| #include <stdlib.h> |
| #include <math.h> |
| #include "dering.h" |
| |
| const od_dering_opt_vtbl OD_DERING_VTBL_C = { |
| { od_filter_dering_direction_4x4_c, od_filter_dering_direction_8x8_c }, |
| { od_filter_dering_orthogonal_4x4_c, od_filter_dering_orthogonal_8x8_c } |
| }; |
| |
| /* Generated from gen_filter_tables.c. */ |
| const int OD_DIRECTION_OFFSETS_TABLE[8][3] = { |
| { -1 * OD_FILT_BSTRIDE + 1, -2 * OD_FILT_BSTRIDE + 2, |
| -3 * OD_FILT_BSTRIDE + 3 }, |
| { 0 * OD_FILT_BSTRIDE + 1, -1 * OD_FILT_BSTRIDE + 2, |
| -1 * OD_FILT_BSTRIDE + 3 }, |
| { 0 * OD_FILT_BSTRIDE + 1, 0 * OD_FILT_BSTRIDE + 2, 0 * OD_FILT_BSTRIDE + 3 }, |
| { 0 * OD_FILT_BSTRIDE + 1, 1 * OD_FILT_BSTRIDE + 2, 1 * OD_FILT_BSTRIDE + 3 }, |
| { 1 * OD_FILT_BSTRIDE + 1, 2 * OD_FILT_BSTRIDE + 2, 3 * OD_FILT_BSTRIDE + 3 }, |
| { 1 * OD_FILT_BSTRIDE + 0, 2 * OD_FILT_BSTRIDE + 1, 3 * OD_FILT_BSTRIDE + 1 }, |
| { 1 * OD_FILT_BSTRIDE + 0, 2 * OD_FILT_BSTRIDE + 0, 3 * OD_FILT_BSTRIDE + 0 }, |
| { 1 * OD_FILT_BSTRIDE + 0, 2 * OD_FILT_BSTRIDE - 1, 3 * OD_FILT_BSTRIDE - 1 }, |
| }; |
| |
| /* Detect direction. 0 means 45-degree up-right, 2 is horizontal, and so on. |
| The search minimizes the weighted variance along all the lines in a |
| particular direction, i.e. the squared error between the input and a |
| "predicted" block where each pixel is replaced by the average along a line |
| in a particular direction. Since each direction have the same sum(x^2) term, |
| that term is never computed. See Section 2, step 2, of: |
| http://jmvalin.ca/notes/intra_paint.pdf */ |
| static int od_dir_find8(const od_dering_in *img, int stride, int32_t *var, |
| int coeff_shift) { |
| int i; |
| int32_t cost[8] = { 0 }; |
| int partial[8][15] = { { 0 } }; |
| int32_t best_cost = 0; |
| int best_dir = 0; |
| /* Instead of dividing by n between 2 and 8, we multiply by 3*5*7*8/n. |
| The output is then 840 times larger, but we don't care for finding |
| the max. */ |
| static const int div_table[] = { 0, 840, 420, 280, 210, 168, 140, 120, 105 }; |
| for (i = 0; i < 8; i++) { |
| int j; |
| for (j = 0; j < 8; j++) { |
| int x; |
| /* We subtract 128 here to reduce the maximum range of the squared |
| partial sums. */ |
| x = (img[i * stride + j] >> coeff_shift) - 128; |
| partial[0][i + j] += x; |
| partial[1][i + j / 2] += x; |
| partial[2][i] += x; |
| partial[3][3 + i - j / 2] += x; |
| partial[4][7 + i - j] += x; |
| partial[5][3 - i / 2 + j] += x; |
| partial[6][j] += x; |
| partial[7][i / 2 + j] += x; |
| } |
| } |
| for (i = 0; i < 8; i++) { |
| cost[2] += partial[2][i] * partial[2][i]; |
| cost[6] += partial[6][i] * partial[6][i]; |
| } |
| cost[2] *= div_table[8]; |
| cost[6] *= div_table[8]; |
| for (i = 0; i < 7; i++) { |
| cost[0] += (partial[0][i] * partial[0][i] + |
| partial[0][14 - i] * partial[0][14 - i]) * |
| div_table[i + 1]; |
| cost[4] += (partial[4][i] * partial[4][i] + |
| partial[4][14 - i] * partial[4][14 - i]) * |
| div_table[i + 1]; |
| } |
| cost[0] += partial[0][7] * partial[0][7] * div_table[8]; |
| cost[4] += partial[4][7] * partial[4][7] * div_table[8]; |
| for (i = 1; i < 8; i += 2) { |
| int j; |
| for (j = 0; j < 4 + 1; j++) { |
| cost[i] += partial[i][3 + j] * partial[i][3 + j]; |
| } |
| cost[i] *= div_table[8]; |
| for (j = 0; j < 4 - 1; j++) { |
| cost[i] += (partial[i][j] * partial[i][j] + |
| partial[i][10 - j] * partial[i][10 - j]) * |
| div_table[2 * j + 2]; |
| } |
| } |
| for (i = 0; i < 8; i++) { |
| if (cost[i] > best_cost) { |
| best_cost = cost[i]; |
| best_dir = i; |
| } |
| } |
| /* Difference between the optimal variance and the variance along the |
| orthogonal direction. Again, the sum(x^2) terms cancel out. */ |
| *var = best_cost - cost[(best_dir + 4) & 7]; |
| /* We'd normally divide by 840, but dividing by 1024 is close enough |
| for what we're going to do with this. */ |
| *var >>= 10; |
| return best_dir; |
| } |
| |
| #define OD_DERING_VERY_LARGE (30000) |
| #define OD_DERING_INBUF_SIZE \ |
| ((OD_BSIZE_MAX + 2 * OD_FILT_BORDER) * (OD_BSIZE_MAX + 2 * OD_FILT_BORDER)) |
| |
| /* Smooth in the direction detected. */ |
| void od_filter_dering_direction_c(int16_t *y, int ystride, const int16_t *in, |
| int ln, int threshold, int dir) { |
| int i; |
| int j; |
| int k; |
| static const int taps[3] = { 3, 2, 1 }; |
| for (i = 0; i < 1 << ln; i++) { |
| for (j = 0; j < 1 << ln; j++) { |
| int16_t sum; |
| int16_t xx; |
| int16_t yy; |
| xx = in[i * OD_FILT_BSTRIDE + j]; |
| sum = 0; |
| for (k = 0; k < 3; k++) { |
| int16_t p0; |
| int16_t p1; |
| p0 = in[i * OD_FILT_BSTRIDE + j + OD_DIRECTION_OFFSETS_TABLE[dir][k]] - |
| xx; |
| p1 = in[i * OD_FILT_BSTRIDE + j - OD_DIRECTION_OFFSETS_TABLE[dir][k]] - |
| xx; |
| if (abs(p0) < threshold) sum += taps[k] * p0; |
| if (abs(p1) < threshold) sum += taps[k] * p1; |
| } |
| yy = xx + ((sum + 8) >> 4); |
| y[i * ystride + j] = yy; |
| } |
| } |
| } |
| |
| void od_filter_dering_direction_4x4_c(int16_t *y, int ystride, |
| const int16_t *in, int threshold, |
| int dir) { |
| od_filter_dering_direction_c(y, ystride, in, 2, threshold, dir); |
| } |
| |
| void od_filter_dering_direction_8x8_c(int16_t *y, int ystride, |
| const int16_t *in, int threshold, |
| int dir) { |
| od_filter_dering_direction_c(y, ystride, in, 3, threshold, dir); |
| } |
| |
| /* Smooth in the direction orthogonal to what was detected. */ |
| void od_filter_dering_orthogonal_c(int16_t *y, int ystride, const int16_t *in, |
| const od_dering_in *x, int xstride, int ln, |
| int threshold, int dir) { |
| int i; |
| int j; |
| int offset; |
| if (dir > 0 && dir < 4) |
| offset = OD_FILT_BSTRIDE; |
| else |
| offset = 1; |
| for (i = 0; i < 1 << ln; i++) { |
| for (j = 0; j < 1 << ln; j++) { |
| int16_t athresh; |
| int16_t yy; |
| int16_t sum; |
| int16_t p; |
| /* Deringing orthogonal to the direction uses a tighter threshold |
| because we want to be conservative. We've presumably already |
| achieved some deringing, so the amount of change is expected |
| to be low. Also, since we might be filtering across an edge, we |
| want to make sure not to blur it. That being said, we might want |
| to be a little bit more aggressive on pure horizontal/vertical |
| since the ringing there tends to be directional, so it doesn't |
| get removed by the directional filtering. */ |
| athresh = OD_MINI( |
| threshold, threshold / 3 + |
| abs(in[i * OD_FILT_BSTRIDE + j] - x[i * xstride + j])); |
| yy = in[i * OD_FILT_BSTRIDE + j]; |
| sum = 0; |
| p = in[i * OD_FILT_BSTRIDE + j + offset] - yy; |
| if (abs(p) < athresh) sum += p; |
| p = in[i * OD_FILT_BSTRIDE + j - offset] - yy; |
| if (abs(p) < athresh) sum += p; |
| p = in[i * OD_FILT_BSTRIDE + j + 2 * offset] - yy; |
| if (abs(p) < athresh) sum += p; |
| p = in[i * OD_FILT_BSTRIDE + j - 2 * offset] - yy; |
| if (abs(p) < athresh) sum += p; |
| y[i * ystride + j] = yy + ((3 * sum + 8) >> 4); |
| } |
| } |
| } |
| |
| void od_filter_dering_orthogonal_4x4_c(int16_t *y, int ystride, |
| const int16_t *in, const od_dering_in *x, |
| int xstride, int threshold, int dir) { |
| od_filter_dering_orthogonal_c(y, ystride, in, x, xstride, 2, threshold, dir); |
| } |
| |
| void od_filter_dering_orthogonal_8x8_c(int16_t *y, int ystride, |
| const int16_t *in, const od_dering_in *x, |
| int xstride, int threshold, int dir) { |
| od_filter_dering_orthogonal_c(y, ystride, in, x, xstride, 3, threshold, dir); |
| } |
| |
| /* This table approximates x^0.16 with the index being log2(x). It is clamped |
| to [-.5, 3]. The table is computed as: |
| round(256*min(3, max(.5, 1.08*(sqrt(2)*2.^([0:17]+8)/256/256).^.16))) */ |
| static const int16_t OD_THRESH_TABLE_Q8[18] = { |
| 128, 134, 150, 168, 188, 210, 234, 262, 292, |
| 327, 365, 408, 455, 509, 569, 635, 710, 768, |
| }; |
| |
| /* Compute deringing filter threshold for each 8x8 block based on the |
| directional variance difference. A high variance difference means that we |
| have a highly directional pattern (e.g. a high contrast edge), so we can |
| apply more deringing. A low variance means that we either have a low |
| contrast edge, or a non-directional texture, so we want to be careful not |
| to blur. */ |
| static void od_compute_thresh(int thresh[OD_DERING_NBLOCKS][OD_DERING_NBLOCKS], |
| int threshold, |
| int32_t var[OD_DERING_NBLOCKS][OD_DERING_NBLOCKS], |
| int nhb, int nvb) { |
| int bx; |
| int by; |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| int v1; |
| /* We use the variance of 8x8 blocks to adjust the threshold. */ |
| v1 = OD_MINI(32767, var[by][bx] >> 6); |
| thresh[by][bx] = (threshold * OD_THRESH_TABLE_Q8[OD_ILOG(v1)] + 128) >> 8; |
| } |
| } |
| } |
| |
| void od_dering(const od_dering_opt_vtbl *vtbl, int16_t *y, int ystride, |
| const od_dering_in *x, int xstride, int nhb, int nvb, int sbx, |
| int sby, int nhsb, int nvsb, int xdec, |
| int dir[OD_DERING_NBLOCKS][OD_DERING_NBLOCKS], int pli, |
| unsigned char *bskip, int skip_stride, int threshold, |
| int coeff_shift) { |
| int i; |
| int j; |
| int bx; |
| int by; |
| int16_t inbuf[OD_DERING_INBUF_SIZE]; |
| int16_t *in; |
| int bsize; |
| int32_t var[OD_DERING_NBLOCKS][OD_DERING_NBLOCKS]; |
| int thresh[OD_DERING_NBLOCKS][OD_DERING_NBLOCKS]; |
| bsize = 3 - xdec; |
| in = inbuf + OD_FILT_BORDER * OD_FILT_BSTRIDE + OD_FILT_BORDER; |
| /* We avoid filtering the pixels for which some of the pixels to average |
| are outside the frame. We could change the filter instead, but it would |
| add special cases for any future vectorization. */ |
| for (i = 0; i < OD_DERING_INBUF_SIZE; i++) inbuf[i] = OD_DERING_VERY_LARGE; |
| for (i = -OD_FILT_BORDER * (sby != 0); |
| i < (nvb << bsize) + OD_FILT_BORDER * (sby != nvsb - 1); i++) { |
| for (j = -OD_FILT_BORDER * (sbx != 0); |
| j < (nhb << bsize) + OD_FILT_BORDER * (sbx != nhsb - 1); j++) { |
| in[i * OD_FILT_BSTRIDE + j] = x[i * xstride + j]; |
| } |
| } |
| /* Assume deringing filter is sparsely applied, so do one large copy rather |
| than small copies later if deringing is skipped. */ |
| for (i = 0; i < nvb << bsize; i++) { |
| for (j = 0; j < nhb << bsize; j++) { |
| y[i * ystride + j] = in[i * OD_FILT_BSTRIDE + j]; |
| } |
| } |
| if (pli == 0) { |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| dir[by][bx] = od_dir_find8(&x[8 * by * xstride + 8 * bx], xstride, |
| &var[by][bx], coeff_shift); |
| } |
| } |
| od_compute_thresh(thresh, threshold, var, nhb, nvb); |
| } else { |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| thresh[by][bx] = threshold; |
| } |
| } |
| } |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| if (bskip[by * skip_stride + bx]) thresh[by][bx] = 0; |
| } |
| } |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| if (thresh[by][bx] == 0) continue; |
| (vtbl->filter_dering_direction[bsize - OD_LOG_BSIZE0])( |
| &y[(by * ystride << bsize) + (bx << bsize)], ystride, |
| &in[(by * OD_FILT_BSTRIDE << bsize) + (bx << bsize)], thresh[by][bx], |
| dir[by][bx]); |
| } |
| } |
| for (i = 0; i < nvb << bsize; i++) { |
| for (j = 0; j < nhb << bsize; j++) { |
| in[i * OD_FILT_BSTRIDE + j] = y[i * ystride + j]; |
| } |
| } |
| for (by = 0; by < nvb; by++) { |
| for (bx = 0; bx < nhb; bx++) { |
| if (thresh[by][bx] == 0) continue; |
| (vtbl->filter_dering_orthogonal[bsize - OD_LOG_BSIZE0])( |
| &y[(by * ystride << bsize) + (bx << bsize)], ystride, |
| &in[(by * OD_FILT_BSTRIDE << bsize) + (bx << bsize)], |
| &x[(by * xstride << bsize) + (bx << bsize)], xstride, thresh[by][bx], |
| dir[by][bx]); |
| } |
| } |
| } |
