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Diffstat (limited to '')
| -rw-r--r-- | third_party/aom/av1/common/cdef_block.c | 257 |
1 files changed, 257 insertions, 0 deletions
diff --git a/third_party/aom/av1/common/cdef_block.c b/third_party/aom/av1/common/cdef_block.c new file mode 100644 index 0000000000..df1de89be3 --- /dev/null +++ b/third_party/aom/av1/common/cdef_block.c @@ -0,0 +1,257 @@ +/* + * 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, + AOM_UNUSED int max_unused, 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, + (256 << coeff_shift) - 1, 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, (256 << coeff_shift) - 1, + coeff_shift); + } +} |