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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
commit | 26a029d407be480d791972afb5975cf62c9360a6 (patch) | |
tree | f435a8308119effd964b339f76abb83a57c29483 /third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c | |
parent | Initial commit. (diff) | |
download | firefox-26a029d407be480d791972afb5975cf62c9360a6.tar.xz firefox-26a029d407be480d791972afb5975cf62c9360a6.zip |
Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c')
-rw-r--r-- | third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c | 562 |
1 files changed, 562 insertions, 0 deletions
diff --git a/third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c b/third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c new file mode 100644 index 0000000000..88e176f56c --- /dev/null +++ b/third_party/aom/av1/encoder/arm/neon/highbd_temporal_filter_neon.c @@ -0,0 +1,562 @@ +/* + * Copyright (c) 2023, 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 <arm_neon.h> + +#include "config/aom_config.h" +#include "config/av1_rtcd.h" +#include "av1/encoder/encoder.h" +#include "av1/encoder/temporal_filter.h" +#include "aom_dsp/mathutils.h" +#include "aom_dsp/arm/mem_neon.h" +#include "aom_dsp/arm/sum_neon.h" + +static INLINE void get_squared_error( + const uint16_t *frame1, const uint32_t stride1, const uint16_t *frame2, + const uint32_t stride2, const uint32_t block_width, + const uint32_t block_height, uint32_t *frame_sse, + const unsigned int dst_stride) { + uint32_t *dst = frame_sse; + + uint32_t i = 0; + do { + uint32_t j = 0; + do { + uint16x8_t s = vld1q_u16(frame1 + i * stride1 + j); + uint16x8_t r = vld1q_u16(frame2 + i * stride2 + j); + + uint16x8_t abs_diff = vabdq_u16(s, r); + uint32x4_t sse_lo = + vmull_u16(vget_low_u16(abs_diff), vget_low_u16(abs_diff)); + uint32x4_t sse_hi = + vmull_u16(vget_high_u16(abs_diff), vget_high_u16(abs_diff)); + + vst1q_u32(dst + j, sse_lo); + vst1q_u32(dst + j + 4, sse_hi); + + j += 8; + } while (j < block_width); + + dst += dst_stride; + i++; + } while (i < block_height); +} + +static uint32_t sum_kernel5x5_mask_single(const uint32x4_t vsrc[5][2], + const uint32x4_t mask_single) { + uint32x4_t vsums = vmulq_u32(vsrc[0][0], mask_single); + vsums = vmlaq_u32(vsums, vsrc[1][0], mask_single); + vsums = vmlaq_u32(vsums, vsrc[2][0], mask_single); + vsums = vmlaq_u32(vsums, vsrc[3][0], mask_single); + vsums = vmlaq_u32(vsums, vsrc[4][0], mask_single); + return horizontal_add_u32x4(vsums); +} + +static uint32x4_t sum_kernel5x5_mask_double(const uint32x4_t vsrc[5][2], + const uint32x4_t mask1, + const uint32x4_t mask2) { + uint32x4_t vsums = vmulq_u32(vsrc[0][0], mask1); + vsums = vmlaq_u32(vsums, vsrc[1][0], mask1); + vsums = vmlaq_u32(vsums, vsrc[2][0], mask1); + vsums = vmlaq_u32(vsums, vsrc[3][0], mask1); + vsums = vmlaq_u32(vsums, vsrc[4][0], mask1); + vsums = vmlaq_u32(vsums, vsrc[0][1], mask2); + vsums = vmlaq_u32(vsums, vsrc[1][1], mask2); + vsums = vmlaq_u32(vsums, vsrc[2][1], mask2); + vsums = vmlaq_u32(vsums, vsrc[3][1], mask2); + vsums = vmlaq_u32(vsums, vsrc[4][1], mask2); + return vsums; +} + +static void highbd_apply_temporal_filter( + const uint16_t *frame, const unsigned int stride, + const uint32_t block_width, const uint32_t block_height, + const int *subblock_mses, unsigned int *accumulator, uint16_t *count, + const uint32_t *frame_sse, const uint32_t frame_sse_stride, + const uint32_t *luma_sse_sum, const double inv_num_ref_pixels, + const double decay_factor, const double inv_factor, + const double weight_factor, const double *d_factor, int tf_wgt_calc_lvl, + int bd) { + assert(((block_width == 16) || (block_width == 32)) && + ((block_height == 16) || (block_height == 32))); + + uint32_t acc_5x5_neon[BH][BW] = { 0 }; + const int half_window = TF_WINDOW_LENGTH >> 1; + + uint32x4_t vsrc[5][2] = { 0 }; + const uint32x4_t k0000 = vdupq_n_u32(0); + const uint32x4_t k1111 = vdupq_n_u32(1); + const uint32_t k3110_u32[4] = { 0, 1, 1, 3 }; + const uint32_t k2111_u32[4] = { 1, 1, 1, 2 }; + const uint32_t k1112_u32[4] = { 2, 1, 1, 1 }; + const uint32_t k0113_u32[4] = { 3, 1, 1, 0 }; + const uint32x4_t k3110 = vld1q_u32(k3110_u32); + const uint32x4_t k2111 = vld1q_u32(k2111_u32); + const uint32x4_t k1112 = vld1q_u32(k1112_u32); + const uint32x4_t k0113 = vld1q_u32(k0113_u32); + + uint32x4_t vmask1[4], vmask2[4]; + vmask1[0] = k1111; + vmask2[0] = vextq_u32(k1111, k0000, 3); + vmask1[1] = vextq_u32(k0000, k1111, 3); + vmask2[1] = vextq_u32(k1111, k0000, 2); + vmask1[2] = vextq_u32(k0000, k1111, 2); + vmask2[2] = vextq_u32(k1111, k0000, 1); + vmask1[3] = vextq_u32(k0000, k1111, 1); + vmask2[3] = k1111; + + uint32_t row = 0; + do { + uint32_t col = 0; + const uint32_t *src = frame_sse + row * frame_sse_stride; + if (row == 0) { + vsrc[2][0] = vld1q_u32(src); + vsrc[3][0] = vld1q_u32(src + frame_sse_stride); + vsrc[4][0] = vld1q_u32(src + 2 * frame_sse_stride); + + // First 2 rows of the 5x5 matrix are padded from the 1st. + vsrc[0][0] = vsrc[2][0]; + vsrc[1][0] = vsrc[2][0]; + } else if (row == 1) { + vsrc[1][0] = vld1q_u32(src - frame_sse_stride); + vsrc[2][0] = vld1q_u32(src); + vsrc[3][0] = vld1q_u32(src + frame_sse_stride); + vsrc[4][0] = vld1q_u32(src + 2 * frame_sse_stride); + + // First row of the 5x5 matrix are padded from the 1st. + vsrc[0][0] = vsrc[1][0]; + } else if (row == block_height - 2) { + vsrc[0][0] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][0] = vld1q_u32(src - frame_sse_stride); + vsrc[2][0] = vld1q_u32(src); + vsrc[3][0] = vld1q_u32(src + frame_sse_stride); + + // Last row of the 5x5 matrix are padded from the one before. + vsrc[4][0] = vsrc[3][0]; + } else if (row == block_height - 1) { + vsrc[0][0] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][0] = vld1q_u32(src - frame_sse_stride); + vsrc[2][0] = vld1q_u32(src); + + // Last 2 rows of the 5x5 matrix are padded from the 3rd. + vsrc[3][0] = vsrc[2][0]; + vsrc[4][0] = vsrc[2][0]; + } else { + vsrc[0][0] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][0] = vld1q_u32(src - frame_sse_stride); + vsrc[2][0] = vld1q_u32(src); + vsrc[3][0] = vld1q_u32(src + frame_sse_stride); + vsrc[4][0] = vld1q_u32(src + 2 * frame_sse_stride); + } + + acc_5x5_neon[row][0] = sum_kernel5x5_mask_single(vsrc, k0113); + acc_5x5_neon[row][1] = sum_kernel5x5_mask_single(vsrc, k1112); + + col += 4; + src += 4; + // Traverse 4 columns at a time + do { + if (row == 0) { + vsrc[2][1] = vld1q_u32(src); + vsrc[3][1] = vld1q_u32(src + frame_sse_stride); + vsrc[4][1] = vld1q_u32(src + 2 * frame_sse_stride); + + // First 2 rows of the 5x5 matrix are padded from the 1st. + vsrc[0][1] = vsrc[2][1]; + vsrc[1][1] = vsrc[2][1]; + } else if (row == 1) { + vsrc[1][1] = vld1q_u32(src - frame_sse_stride); + vsrc[2][1] = vld1q_u32(src); + vsrc[3][1] = vld1q_u32(src + frame_sse_stride); + vsrc[4][1] = vld1q_u32(src + 2 * frame_sse_stride); + + // First row of the 5x5 matrix are padded from the 1st. + vsrc[0][1] = vsrc[1][1]; + } else if (row == block_height - 2) { + vsrc[0][1] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][1] = vld1q_u32(src - frame_sse_stride); + vsrc[2][1] = vld1q_u32(src); + vsrc[3][1] = vld1q_u32(src + frame_sse_stride); + + // Last row of the 5x5 matrix are padded from the one before. + vsrc[4][1] = vsrc[3][1]; + } else if (row == block_height - 1) { + vsrc[0][1] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][1] = vld1q_u32(src - frame_sse_stride); + vsrc[2][1] = vld1q_u32(src); + + // Last 2 rows of the 5x5 matrix are padded from the 3rd. + vsrc[3][1] = vsrc[2][1]; + vsrc[4][1] = vsrc[2][1]; + } else { + vsrc[0][1] = vld1q_u32(src - 2 * frame_sse_stride); + vsrc[1][1] = vld1q_u32(src - frame_sse_stride); + vsrc[2][1] = vld1q_u32(src); + vsrc[3][1] = vld1q_u32(src + frame_sse_stride); + vsrc[4][1] = vld1q_u32(src + 2 * frame_sse_stride); + } + + uint32x4_t sums[4]; + sums[0] = sum_kernel5x5_mask_double(vsrc, vmask1[0], vmask2[0]); + sums[1] = sum_kernel5x5_mask_double(vsrc, vmask1[1], vmask2[1]); + sums[2] = sum_kernel5x5_mask_double(vsrc, vmask1[2], vmask2[2]); + sums[3] = sum_kernel5x5_mask_double(vsrc, vmask1[3], vmask2[3]); + vst1q_u32(&acc_5x5_neon[row][col - half_window], + horizontal_add_4d_u32x4(sums)); + + vsrc[0][0] = vsrc[0][1]; + vsrc[1][0] = vsrc[1][1]; + vsrc[2][0] = vsrc[2][1]; + vsrc[3][0] = vsrc[3][1]; + vsrc[4][0] = vsrc[4][1]; + + src += 4; + col += 4; + } while (col <= block_width - 4); + + acc_5x5_neon[row][col - half_window] = + sum_kernel5x5_mask_single(vsrc, k2111); + acc_5x5_neon[row][col - half_window + 1] = + sum_kernel5x5_mask_single(vsrc, k3110); + + row++; + } while (row < block_height); + + // Perform filtering. + if (tf_wgt_calc_lvl == 0) { + for (unsigned int i = 0, k = 0; i < block_height; i++) { + for (unsigned int j = 0; j < block_width; j++, k++) { + const int pixel_value = frame[i * stride + j]; + // Scale down the difference for high bit depth input. + const uint32_t diff_sse = + (acc_5x5_neon[i][j] + luma_sse_sum[i * BW + j]) >> ((bd - 8) * 2); + + const double window_error = diff_sse * inv_num_ref_pixels; + const int subblock_idx = + (i >= block_height / 2) * 2 + (j >= block_width / 2); + const double block_error = (double)subblock_mses[subblock_idx]; + const double combined_error = + weight_factor * window_error + block_error * inv_factor; + // Compute filter weight. + double scaled_error = + combined_error * d_factor[subblock_idx] * decay_factor; + scaled_error = AOMMIN(scaled_error, 7); + const int weight = (int)(exp(-scaled_error) * TF_WEIGHT_SCALE); + accumulator[k] += weight * pixel_value; + count[k] += weight; + } + } + } else { + for (unsigned int i = 0, k = 0; i < block_height; i++) { + for (unsigned int j = 0; j < block_width; j++, k++) { + const int pixel_value = frame[i * stride + j]; + // Scale down the difference for high bit depth input. + const uint32_t diff_sse = + (acc_5x5_neon[i][j] + luma_sse_sum[i * BW + j]) >> ((bd - 8) * 2); + + const double window_error = diff_sse * inv_num_ref_pixels; + const int subblock_idx = + (i >= block_height / 2) * 2 + (j >= block_width / 2); + const double block_error = (double)subblock_mses[subblock_idx]; + const double combined_error = + weight_factor * window_error + block_error * inv_factor; + // Compute filter weight. + double scaled_error = + combined_error * d_factor[subblock_idx] * decay_factor; + scaled_error = AOMMIN(scaled_error, 7); + const float fweight = + approx_exp((float)-scaled_error) * TF_WEIGHT_SCALE; + const int weight = iroundpf(fweight); + accumulator[k] += weight * pixel_value; + count[k] += weight; + } + } + } +} + +void av1_highbd_apply_temporal_filter_neon( + const YV12_BUFFER_CONFIG *frame_to_filter, const MACROBLOCKD *mbd, + const BLOCK_SIZE block_size, const int mb_row, const int mb_col, + const int num_planes, const double *noise_levels, const MV *subblock_mvs, + const int *subblock_mses, const int q_factor, const int filter_strength, + int tf_wgt_calc_lvl, const uint8_t *pred8, uint32_t *accum, + uint16_t *count) { + const int is_high_bitdepth = frame_to_filter->flags & YV12_FLAG_HIGHBITDEPTH; + assert(TF_WINDOW_LENGTH == 5 && "Only support window length 5 with Neon!"); + assert(num_planes >= 1 && num_planes <= MAX_MB_PLANE); + (void)is_high_bitdepth; + assert(is_high_bitdepth); + + // Block information. + const int mb_height = block_size_high[block_size]; + const int mb_width = block_size_wide[block_size]; + // Frame information. + const int frame_height = frame_to_filter->y_crop_height; + const int frame_width = frame_to_filter->y_crop_width; + const int min_frame_size = AOMMIN(frame_height, frame_width); + // Variables to simplify combined error calculation. + const double inv_factor = 1.0 / ((TF_WINDOW_BLOCK_BALANCE_WEIGHT + 1) * + TF_SEARCH_ERROR_NORM_WEIGHT); + const double weight_factor = + (double)TF_WINDOW_BLOCK_BALANCE_WEIGHT * inv_factor; + // Adjust filtering based on q. + // Larger q -> stronger filtering -> larger weight. + // Smaller q -> weaker filtering -> smaller weight. + double q_decay = pow((double)q_factor / TF_Q_DECAY_THRESHOLD, 2); + q_decay = CLIP(q_decay, 1e-5, 1); + if (q_factor >= TF_QINDEX_CUTOFF) { + // Max q_factor is 255, therefore the upper bound of q_decay is 8. + // We do not need a clip here. + q_decay = 0.5 * pow((double)q_factor / 64, 2); + } + // Smaller strength -> smaller filtering weight. + double s_decay = pow((double)filter_strength / TF_STRENGTH_THRESHOLD, 2); + s_decay = CLIP(s_decay, 1e-5, 1); + double d_factor[4] = { 0 }; + uint32_t frame_sse[BW * BH] = { 0 }; + uint32_t luma_sse_sum[BW * BH] = { 0 }; + uint16_t *pred = CONVERT_TO_SHORTPTR(pred8); + + for (int subblock_idx = 0; subblock_idx < 4; subblock_idx++) { + // Larger motion vector -> smaller filtering weight. + const MV mv = subblock_mvs[subblock_idx]; + const double distance = sqrt(pow(mv.row, 2) + pow(mv.col, 2)); + double distance_threshold = min_frame_size * TF_SEARCH_DISTANCE_THRESHOLD; + distance_threshold = AOMMAX(distance_threshold, 1); + d_factor[subblock_idx] = distance / distance_threshold; + d_factor[subblock_idx] = AOMMAX(d_factor[subblock_idx], 1); + } + + // Handle planes in sequence. + int plane_offset = 0; + for (int plane = 0; plane < num_planes; ++plane) { + const uint32_t plane_h = mb_height >> mbd->plane[plane].subsampling_y; + const uint32_t plane_w = mb_width >> mbd->plane[plane].subsampling_x; + const uint32_t frame_stride = + frame_to_filter->strides[plane == AOM_PLANE_Y ? 0 : 1]; + const uint32_t frame_sse_stride = plane_w; + const int frame_offset = mb_row * plane_h * frame_stride + mb_col * plane_w; + + const uint16_t *ref = + CONVERT_TO_SHORTPTR(frame_to_filter->buffers[plane]) + frame_offset; + const int ss_x_shift = + mbd->plane[plane].subsampling_x - mbd->plane[AOM_PLANE_Y].subsampling_x; + const int ss_y_shift = + mbd->plane[plane].subsampling_y - mbd->plane[AOM_PLANE_Y].subsampling_y; + const int num_ref_pixels = TF_WINDOW_LENGTH * TF_WINDOW_LENGTH + + ((plane) ? (1 << (ss_x_shift + ss_y_shift)) : 0); + const double inv_num_ref_pixels = 1.0 / num_ref_pixels; + // Larger noise -> larger filtering weight. + const double n_decay = 0.5 + log(2 * noise_levels[plane] + 5.0); + // Decay factors for non-local mean approach. + const double decay_factor = 1 / (n_decay * q_decay * s_decay); + + // Filter U-plane and V-plane using Y-plane. This is because motion + // search is only done on Y-plane, so the information from Y-plane + // will be more accurate. The luma sse sum is reused in both chroma + // planes. + if (plane == AOM_PLANE_U) { + for (unsigned int i = 0; i < plane_h; i++) { + for (unsigned int j = 0; j < plane_w; j++) { + for (int ii = 0; ii < (1 << ss_y_shift); ++ii) { + for (int jj = 0; jj < (1 << ss_x_shift); ++jj) { + const int yy = (i << ss_y_shift) + ii; // Y-coord on Y-plane. + const int xx = (j << ss_x_shift) + jj; // X-coord on Y-plane. + const int ww = frame_sse_stride + << ss_x_shift; // Width of Y-plane. + luma_sse_sum[i * BW + j] += frame_sse[yy * ww + xx]; + } + } + } + } + } + get_squared_error(ref, frame_stride, pred + plane_offset, plane_w, plane_w, + plane_h, frame_sse, frame_sse_stride); + + highbd_apply_temporal_filter( + pred + plane_offset, plane_w, plane_w, plane_h, subblock_mses, + accum + plane_offset, count + plane_offset, frame_sse, frame_sse_stride, + luma_sse_sum, inv_num_ref_pixels, decay_factor, inv_factor, + weight_factor, d_factor, tf_wgt_calc_lvl, mbd->bd); + + plane_offset += plane_h * plane_w; + } +} + +double av1_highbd_estimate_noise_from_single_plane_neon(const uint16_t *src, + int height, int width, + int stride, + int bitdepth, + int edge_thresh) { + uint16x8_t thresh = vdupq_n_u16(edge_thresh); + uint64x2_t acc = vdupq_n_u64(0); + // Count is in theory positive as it counts the number of times we're under + // the threshold, but it will be counted negatively in order to make best use + // of the vclt instruction, which sets every bit of a lane to 1 when the + // condition is true. + int32x4_t count = vdupq_n_s32(0); + int final_count = 0; + uint64_t final_acc = 0; + const uint16_t *src_start = src + stride + 1; + int h = 1; + + do { + int w = 1; + const uint16_t *src_ptr = src_start; + + while (w <= (width - 1) - 8) { + uint16x8_t mat[3][3]; + mat[0][0] = vld1q_u16(src_ptr - stride - 1); + mat[0][1] = vld1q_u16(src_ptr - stride); + mat[0][2] = vld1q_u16(src_ptr - stride + 1); + mat[1][0] = vld1q_u16(src_ptr - 1); + mat[1][1] = vld1q_u16(src_ptr); + mat[1][2] = vld1q_u16(src_ptr + 1); + mat[2][0] = vld1q_u16(src_ptr + stride - 1); + mat[2][1] = vld1q_u16(src_ptr + stride); + mat[2][2] = vld1q_u16(src_ptr + stride + 1); + + // Compute Sobel gradients. + uint16x8_t gxa = vaddq_u16(mat[0][0], mat[2][0]); + uint16x8_t gxb = vaddq_u16(mat[0][2], mat[2][2]); + gxa = vaddq_u16(gxa, vaddq_u16(mat[1][0], mat[1][0])); + gxb = vaddq_u16(gxb, vaddq_u16(mat[1][2], mat[1][2])); + + uint16x8_t gya = vaddq_u16(mat[0][0], mat[0][2]); + uint16x8_t gyb = vaddq_u16(mat[2][0], mat[2][2]); + gya = vaddq_u16(gya, vaddq_u16(mat[0][1], mat[0][1])); + gyb = vaddq_u16(gyb, vaddq_u16(mat[2][1], mat[2][1])); + + uint16x8_t ga = vabaq_u16(vabdq_u16(gxa, gxb), gya, gyb); + ga = vrshlq_u16(ga, vdupq_n_s16(8 - bitdepth)); + + // Check which vector elements are under the threshold. The Laplacian is + // then unconditionnally computed and we accumulate zeros if we're not + // under the threshold. This is much faster than using an if statement. + uint16x8_t thresh_u16 = vcltq_u16(ga, thresh); + + uint16x8_t center = vshlq_n_u16(mat[1][1], 2); + + uint16x8_t adj0 = vaddq_u16(mat[0][1], mat[2][1]); + uint16x8_t adj1 = vaddq_u16(mat[1][0], mat[1][2]); + uint16x8_t adj = vaddq_u16(adj0, adj1); + adj = vaddq_u16(adj, adj); + + uint16x8_t diag0 = vaddq_u16(mat[0][0], mat[0][2]); + uint16x8_t diag1 = vaddq_u16(mat[2][0], mat[2][2]); + uint16x8_t diag = vaddq_u16(diag0, diag1); + + uint16x8_t v = vabdq_u16(vaddq_u16(center, diag), adj); + v = vandq_u16(vrshlq_u16(v, vdupq_n_s16(8 - bitdepth)), thresh_u16); + uint32x4_t v_u32 = vpaddlq_u16(v); + + acc = vpadalq_u32(acc, v_u32); + // Add -1 for each lane where the gradient is under the threshold. + count = vpadalq_s16(count, vreinterpretq_s16_u16(thresh_u16)); + + w += 8; + src_ptr += 8; + } + + if (w <= (width - 1) - 4) { + uint16x4_t mat[3][3]; + mat[0][0] = vld1_u16(src_ptr - stride - 1); + mat[0][1] = vld1_u16(src_ptr - stride); + mat[0][2] = vld1_u16(src_ptr - stride + 1); + mat[1][0] = vld1_u16(src_ptr - 1); + mat[1][1] = vld1_u16(src_ptr); + mat[1][2] = vld1_u16(src_ptr + 1); + mat[2][0] = vld1_u16(src_ptr + stride - 1); + mat[2][1] = vld1_u16(src_ptr + stride); + mat[2][2] = vld1_u16(src_ptr + stride + 1); + + // Compute Sobel gradients. + uint16x4_t gxa = vadd_u16(mat[0][0], mat[2][0]); + uint16x4_t gxb = vadd_u16(mat[0][2], mat[2][2]); + gxa = vadd_u16(gxa, vadd_u16(mat[1][0], mat[1][0])); + gxb = vadd_u16(gxb, vadd_u16(mat[1][2], mat[1][2])); + + uint16x4_t gya = vadd_u16(mat[0][0], mat[0][2]); + uint16x4_t gyb = vadd_u16(mat[2][0], mat[2][2]); + gya = vadd_u16(gya, vadd_u16(mat[0][1], mat[0][1])); + gyb = vadd_u16(gyb, vadd_u16(mat[2][1], mat[2][1])); + + uint16x4_t ga = vaba_u16(vabd_u16(gxa, gxb), gya, gyb); + ga = vrshl_u16(ga, vdup_n_s16(8 - bitdepth)); + + // Check which vector elements are under the threshold. The Laplacian is + // then unconditionnally computed and we accumulate zeros if we're not + // under the threshold. This is much faster than using an if statement. + uint16x4_t thresh_u16 = vclt_u16(ga, vget_low_u16(thresh)); + + uint16x4_t center = vshl_n_u16(mat[1][1], 2); + + uint16x4_t adj0 = vadd_u16(mat[0][1], mat[2][1]); + uint16x4_t adj1 = vadd_u16(mat[1][0], mat[1][2]); + uint16x4_t adj = vadd_u16(adj0, adj1); + adj = vadd_u16(adj, adj); + + uint16x4_t diag0 = vadd_u16(mat[0][0], mat[0][2]); + uint16x4_t diag1 = vadd_u16(mat[2][0], mat[2][2]); + uint16x4_t diag = vadd_u16(diag0, diag1); + + uint16x4_t v = vabd_u16(vadd_u16(center, diag), adj); + v = vand_u16(v, thresh_u16); + uint32x4_t v_u32 = vmovl_u16(vrshl_u16(v, vdup_n_s16(8 - bitdepth))); + + acc = vpadalq_u32(acc, v_u32); + // Add -1 for each lane where the gradient is under the threshold. + count = vaddw_s16(count, vreinterpret_s16_u16(thresh_u16)); + + w += 4; + src_ptr += 4; + } + + while (w < width - 1) { + int mat[3][3]; + mat[0][0] = *(src_ptr - stride - 1); + mat[0][1] = *(src_ptr - stride); + mat[0][2] = *(src_ptr - stride + 1); + mat[1][0] = *(src_ptr - 1); + mat[1][1] = *(src_ptr); + mat[1][2] = *(src_ptr + 1); + mat[2][0] = *(src_ptr + stride - 1); + mat[2][1] = *(src_ptr + stride); + mat[2][2] = *(src_ptr + stride + 1); + + // Compute Sobel gradients. + const int gx = (mat[0][0] - mat[0][2]) + (mat[2][0] - mat[2][2]) + + 2 * (mat[1][0] - mat[1][2]); + const int gy = (mat[0][0] - mat[2][0]) + (mat[0][2] - mat[2][2]) + + 2 * (mat[0][1] - mat[2][1]); + const int ga = ROUND_POWER_OF_TWO(abs(gx) + abs(gy), bitdepth - 8); + + // Accumulate Laplacian. + const int is_under = ga < edge_thresh; + const int v = 4 * mat[1][1] - + 2 * (mat[0][1] + mat[2][1] + mat[1][0] + mat[1][2]) + + (mat[0][0] + mat[0][2] + mat[2][0] + mat[2][2]); + final_acc += ROUND_POWER_OF_TWO(abs(v), bitdepth - 8) * is_under; + final_count += is_under; + + src_ptr++; + w++; + } + src_start += stride; + } while (++h < height - 1); + + // We counted negatively, so subtract to get the final value. + final_count -= horizontal_add_s32x4(count); + final_acc += horizontal_add_u64x2(acc); + return (final_count < 16) + ? -1.0 + : (double)final_acc / (6 * final_count) * SQRT_PI_BY_2; +} |