| /* |
| * 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. |
| */ |
| |
| #include <math.h> |
| #include <stdlib.h> |
| |
| #include "config/aom_dsp_rtcd.h" |
| #include "config/av1_rtcd.h" |
| |
| #include "av1/common/cdef.h" |
| |
| /* Generated from gen_filter_tables.c. */ |
| DECLARE_ALIGNED(16, const int, cdef_directions[8][2]) = { |
| { -1 * CDEF_BSTRIDE + 1, -2 * CDEF_BSTRIDE + 2 }, |
| { 0 * CDEF_BSTRIDE + 1, -1 * CDEF_BSTRIDE + 2 }, |
| { 0 * CDEF_BSTRIDE + 1, 0 * CDEF_BSTRIDE + 2 }, |
| { 0 * CDEF_BSTRIDE + 1, 1 * CDEF_BSTRIDE + 2 }, |
| { 1 * CDEF_BSTRIDE + 1, 2 * CDEF_BSTRIDE + 2 }, |
| { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE + 1 }, |
| { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_BSTRIDE + 0 }, |
| { 1 * CDEF_BSTRIDE + 0, 2 * CDEF_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 */ |
| int cdef_find_dir_c(const uint16_t *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; |
| } |
| |
| const int cdef_pri_taps[2][2] = { { 4, 2 }, { 3, 3 } }; |
| const int cdef_sec_taps[2][2] = { { 2, 1 }, { 2, 1 } }; |
| |
| /* Smooth in the direction detected. */ |
| void cdef_filter_block_c(uint8_t *dst8, uint16_t *dst16, int dstride, |
| const uint16_t *in, int pri_strength, int sec_strength, |
| int dir, int pri_damping, int sec_damping, int bsize, |
| int coeff_shift) { |
| int i, j, k; |
| const int s = CDEF_BSTRIDE; |
| const int *pri_taps = cdef_pri_taps[(pri_strength >> coeff_shift) & 1]; |
| const int *sec_taps = cdef_sec_taps[(pri_strength >> coeff_shift) & 1]; |
| for (i = 0; i < 4 << (bsize == BLOCK_8X8 || bsize == BLOCK_4X8); i++) { |
| for (j = 0; j < 4 << (bsize == BLOCK_8X8 || bsize == BLOCK_8X4); j++) { |
| int16_t sum = 0; |
| int16_t y; |
| int16_t x = in[i * s + j]; |
| int max = x; |
| int min = x; |
| for (k = 0; k < 2; k++) { |
| int16_t p0 = in[i * s + j + cdef_directions[dir][k]]; |
| int16_t p1 = in[i * s + j - cdef_directions[dir][k]]; |
| sum += pri_taps[k] * constrain(p0 - x, pri_strength, pri_damping); |
| sum += pri_taps[k] * constrain(p1 - x, pri_strength, pri_damping); |
| if (p0 != CDEF_VERY_LARGE) max = AOMMAX(p0, max); |
| if (p1 != CDEF_VERY_LARGE) max = AOMMAX(p1, max); |
| min = AOMMIN(p0, min); |
| min = AOMMIN(p1, min); |
| int16_t s0 = in[i * s + j + cdef_directions[(dir + 2) & 7][k]]; |
| int16_t s1 = in[i * s + j - cdef_directions[(dir + 2) & 7][k]]; |
| int16_t s2 = in[i * s + j + cdef_directions[(dir + 6) & 7][k]]; |
| int16_t s3 = in[i * s + j - cdef_directions[(dir + 6) & 7][k]]; |
| if (s0 != CDEF_VERY_LARGE) max = AOMMAX(s0, max); |
| if (s1 != CDEF_VERY_LARGE) max = AOMMAX(s1, max); |
| if (s2 != CDEF_VERY_LARGE) max = AOMMAX(s2, max); |
| if (s3 != CDEF_VERY_LARGE) max = AOMMAX(s3, max); |
| min = AOMMIN(s0, min); |
| min = AOMMIN(s1, min); |
| min = AOMMIN(s2, min); |
| min = AOMMIN(s3, min); |
| sum += sec_taps[k] * constrain(s0 - x, sec_strength, sec_damping); |
| sum += sec_taps[k] * constrain(s1 - x, sec_strength, sec_damping); |
| sum += sec_taps[k] * constrain(s2 - x, sec_strength, sec_damping); |
| sum += sec_taps[k] * constrain(s3 - x, sec_strength, sec_damping); |
| } |
| y = clamp((int16_t)x + ((8 + sum - (sum < 0)) >> 4), min, max); |
| if (dst8) |
| dst8[i * dstride + j] = (uint8_t)y; |
| else |
| dst16[i * dstride + j] = (uint16_t)y; |
| } |
| } |
| } |
| |
| /* Compute the primary filter strength for an 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 INLINE int adjust_strength(int strength, int32_t var) { |
| const int i = var >> 6 ? AOMMIN(get_msb(var >> 6), 12) : 0; |
| /* We use the variance of 8x8 blocks to adjust the strength. */ |
| return var ? (strength * (4 + i) + 8) >> 4 : 0; |
| } |
| |
| void cdef_filter_fb(uint8_t *dst8, uint16_t *dst16, int dstride, uint16_t *in, |
| int xdec, int ydec, int dir[CDEF_NBLOCKS][CDEF_NBLOCKS], |
| int *dirinit, int var[CDEF_NBLOCKS][CDEF_NBLOCKS], int pli, |
| cdef_list *dlist, int cdef_count, int level, |
| int sec_strength, int pri_damping, int sec_damping, |
| int coeff_shift) { |
| int bi; |
| int bx; |
| int by; |
| int bsize, bsizex, bsizey; |
| |
| int pri_strength = level << coeff_shift; |
| sec_strength <<= coeff_shift; |
| sec_damping += coeff_shift - (pli != AOM_PLANE_Y); |
| pri_damping += coeff_shift - (pli != AOM_PLANE_Y); |
| bsize = |
| ydec ? (xdec ? BLOCK_4X4 : BLOCK_8X4) : (xdec ? BLOCK_4X8 : BLOCK_8X8); |
| bsizex = 3 - xdec; |
| bsizey = 3 - ydec; |
| if (dirinit && pri_strength == 0 && sec_strength == 0) { |
| // If we're here, both primary and secondary strengths are 0, and |
| // we still haven't written anything to y[] yet, so we just copy |
| // the input to y[]. This is necessary only for av1_cdef_search() |
| // and only av1_cdef_search() sets dirinit. |
| for (bi = 0; bi < cdef_count; bi++) { |
| by = dlist[bi].by; |
| bx = dlist[bi].bx; |
| int iy, ix; |
| // TODO(stemidts/jmvalin): SIMD optimisations |
| for (iy = 0; iy < 1 << bsizey; iy++) |
| for (ix = 0; ix < 1 << bsizex; ix++) |
| dst16[(bi << (bsizex + bsizey)) + (iy << bsizex) + ix] = |
| in[((by << bsizey) + iy) * CDEF_BSTRIDE + (bx << bsizex) + ix]; |
| } |
| return; |
| } |
| |
| if (pli == 0) { |
| if (!dirinit || !*dirinit) { |
| for (bi = 0; bi < cdef_count; bi++) { |
| by = dlist[bi].by; |
| bx = dlist[bi].bx; |
| dir[by][bx] = cdef_find_dir(&in[8 * by * CDEF_BSTRIDE + 8 * bx], |
| CDEF_BSTRIDE, &var[by][bx], coeff_shift); |
| } |
| if (dirinit) *dirinit = 1; |
| } |
| } |
| if (pli == 1 && xdec != ydec) { |
| for (bi = 0; bi < cdef_count; bi++) { |
| static const int conv422[8] = { 7, 0, 2, 4, 5, 6, 6, 6 }; |
| static const int conv440[8] = { 1, 2, 2, 2, 3, 4, 6, 0 }; |
| by = dlist[bi].by; |
| bx = dlist[bi].bx; |
| dir[by][bx] = (xdec ? conv422 : conv440)[dir[by][bx]]; |
| } |
| } |
| |
| for (bi = 0; bi < cdef_count; bi++) { |
| int t = dlist[bi].skip ? 0 : pri_strength; |
| int s = dlist[bi].skip ? 0 : sec_strength; |
| by = dlist[bi].by; |
| bx = dlist[bi].bx; |
| if (dst8) |
| cdef_filter_block( |
| &dst8[(by << bsizey) * dstride + (bx << bsizex)], NULL, dstride, |
| &in[(by * CDEF_BSTRIDE << bsizey) + (bx << bsizex)], |
| (pli ? t : adjust_strength(t, var[by][bx])), s, t ? dir[by][bx] : 0, |
| pri_damping, sec_damping, bsize, coeff_shift); |
| else |
| cdef_filter_block( |
| NULL, |
| &dst16[dirinit ? bi << (bsizex + bsizey) |
| : (by << bsizey) * dstride + (bx << bsizex)], |
| dirinit ? 1 << bsizex : dstride, |
| &in[(by * CDEF_BSTRIDE << bsizey) + (bx << bsizex)], |
| (pli ? t : adjust_strength(t, var[by][bx])), s, t ? dir[by][bx] : 0, |
| pri_damping, sec_damping, bsize, coeff_shift); |
| } |
| } |