/* * 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 #include #include #include "config/aom_config.h" #include "config/aom_scale_rtcd.h" #include "aom_dsp/aom_dsp_common.h" #include "aom_dsp/mathutils.h" #include "aom_dsp/odintrin.h" #include "aom_mem/aom_mem.h" #include "aom_ports/aom_timer.h" #include "aom_ports/mem.h" #include "av1/common/alloccommon.h" #include "av1/common/av1_common_int.h" #include "av1/common/quant_common.h" #include "av1/common/reconinter.h" #include "av1/encoder/av1_quantize.h" #include "av1/encoder/encodeframe.h" #include "av1/encoder/encoder.h" #include "av1/encoder/ethread.h" #include "av1/encoder/extend.h" #include "av1/encoder/firstpass.h" #include "av1/encoder/gop_structure.h" #include "av1/encoder/intra_mode_search_utils.h" #include "av1/encoder/mcomp.h" #include "av1/encoder/motion_search_facade.h" #include "av1/encoder/pass2_strategy.h" #include "av1/encoder/ratectrl.h" #include "av1/encoder/reconinter_enc.h" #include "av1/encoder/segmentation.h" #include "av1/encoder/temporal_filter.h" /*!\cond */ // NOTE: All `tf` in this file means `temporal filtering`. // Forward Declaration. static void tf_determine_block_partition(const MV block_mv, const int block_mse, MV *subblock_mvs, int *subblock_mses); // This function returns the minimum and maximum log variances for 4x4 sub // blocks in the current block. static inline void get_log_var_4x4sub_blk( AV1_COMP *cpi, const YV12_BUFFER_CONFIG *const frame_to_filter, int mb_row, int mb_col, BLOCK_SIZE block_size, double *blk_4x4_var_min, double *blk_4x4_var_max, int is_hbd) { const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; int var_min = INT_MAX; int var_max = 0; // Derive the source buffer. const int src_stride = frame_to_filter->y_stride; const int y_offset = mb_row * mb_height * src_stride + mb_col * mb_width; const uint8_t *src_buf = frame_to_filter->y_buffer + y_offset; for (int i = 0; i < mb_height; i += MI_SIZE) { for (int j = 0; j < mb_width; j += MI_SIZE) { // Calculate the 4x4 sub-block variance. const int var = av1_calc_normalized_variance( cpi->ppi->fn_ptr[BLOCK_4X4].vf, src_buf + (i * src_stride) + j, src_stride, is_hbd); // Record min and max for over-arching block var_min = AOMMIN(var_min, var); var_max = AOMMAX(var_max, var); } } *blk_4x4_var_min = log1p(var_min / 16.0); *blk_4x4_var_max = log1p(var_max / 16.0); } // Helper function to get `q` used for encoding. static int get_q(const AV1_COMP *cpi) { const GF_GROUP *gf_group = &cpi->ppi->gf_group; const FRAME_TYPE frame_type = gf_group->frame_type[cpi->gf_frame_index]; const int q = (int)av1_convert_qindex_to_q(cpi->ppi->p_rc.avg_frame_qindex[frame_type], cpi->common.seq_params->bit_depth); return q; } /*!\endcond */ /*!\brief Does motion search for blocks in temporal filtering. This is * the first step for temporal filtering. More specifically, given a frame to * be filtered and another frame as reference, this function searches the * reference frame to find out the most similar block as that from the frame * to be filtered. This found block will be further used for weighted * averaging. * * NOTE: Besides doing motion search for the entire block, this function will * also do motion search for each 1/4 sub-block to get more precise * predictions. Then, this function will determines whether to use 4 * sub-blocks to replace the entire block. If we do need to split the * entire block, 4 elements in `subblock_mvs` and `subblock_mses` refer to * the searched motion vector and search error (MSE) w.r.t. each sub-block * respectively. Otherwise, the 4 elements will be the same, all of which * are assigned as the searched motion vector and search error (MSE) for * the entire block. * * \ingroup src_frame_proc * \param[in] cpi Top level encoder instance structure * \param[in] mb Pointer to macroblock * \param[in] frame_to_filter Pointer to the frame to be filtered * \param[in] ref_frame Pointer to the reference frame * \param[in] block_size Block size used for motion search * \param[in] mb_row Row index of the block in the frame * \param[in] mb_col Column index of the block in the frame * \param[in] ref_mv Reference motion vector, which is commonly * inherited from the motion search result of * previous frame. * \param[in] allow_me_for_sub_blks Flag to indicate whether motion search at * 16x16 sub-block level is needed or not. * \param[out] subblock_mvs Pointer to the motion vectors for * 4 sub-blocks * \param[out] subblock_mses Pointer to the search errors (MSE) for * 4 sub-blocks * * \remark Nothing will be returned. Results are saved in subblock_mvs and * subblock_mses */ static void tf_motion_search(AV1_COMP *cpi, MACROBLOCK *mb, const YV12_BUFFER_CONFIG *frame_to_filter, const YV12_BUFFER_CONFIG *ref_frame, const BLOCK_SIZE block_size, const int mb_row, const int mb_col, MV *ref_mv, bool allow_me_for_sub_blks, MV *subblock_mvs, int *subblock_mses) { // Frame information const int min_frame_size = AOMMIN(cpi->common.width, cpi->common.height); // Block information (ONLY Y-plane is used for motion search). const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; const int mb_pels = mb_height * mb_width; const int y_stride = frame_to_filter->y_stride; const int src_width = frame_to_filter->y_width; const int ref_width = ref_frame->y_width; assert(y_stride == ref_frame->y_stride); assert(src_width == ref_width); const int y_offset = mb_row * mb_height * y_stride + mb_col * mb_width; // Save input state. MACROBLOCKD *const mbd = &mb->e_mbd; const struct buf_2d ori_src_buf = mb->plane[0].src; const struct buf_2d ori_pre_buf = mbd->plane[0].pre[0]; // Parameters used for motion search. FULLPEL_MOTION_SEARCH_PARAMS full_ms_params; SUBPEL_MOTION_SEARCH_PARAMS ms_params; const int step_param = av1_init_search_range( AOMMAX(frame_to_filter->y_crop_width, frame_to_filter->y_crop_height)); const SUBPEL_SEARCH_TYPE subpel_search_type = USE_8_TAPS; const int force_integer_mv = cpi->common.features.cur_frame_force_integer_mv; const MV_COST_TYPE mv_cost_type = min_frame_size >= 720 ? MV_COST_L1_HDRES : (min_frame_size >= 480 ? MV_COST_L1_MIDRES : MV_COST_L1_LOWRES); // Starting position for motion search. FULLPEL_MV start_mv = get_fullmv_from_mv(ref_mv); // Baseline position for motion search (used for rate distortion comparison). const MV baseline_mv = kZeroMv; // Setup. mb->plane[0].src.buf = frame_to_filter->y_buffer + y_offset; mb->plane[0].src.stride = y_stride; mb->plane[0].src.width = src_width; mbd->plane[0].pre[0].buf = ref_frame->y_buffer + y_offset; mbd->plane[0].pre[0].stride = y_stride; mbd->plane[0].pre[0].width = ref_width; const SEARCH_METHODS search_method = NSTEP; const search_site_config *search_site_cfg = av1_get_search_site_config(cpi, mb, search_method); // Unused intermediate results for motion search. unsigned int sse, error; int distortion; int cost_list[5]; // Do motion search. int_mv best_mv; // Searched motion vector. FULLPEL_MV_STATS best_mv_stats; int block_mse = INT_MAX; MV block_mv = kZeroMv; const int q = get_q(cpi); av1_make_default_fullpel_ms_params(&full_ms_params, cpi, mb, block_size, &baseline_mv, start_mv, search_site_cfg, search_method, /*fine_search_interval=*/0); full_ms_params.run_mesh_search = 1; full_ms_params.mv_cost_params.mv_cost_type = mv_cost_type; if (cpi->sf.mv_sf.prune_mesh_search == PRUNE_MESH_SEARCH_LVL_1) { // Enable prune_mesh_search based on q for PRUNE_MESH_SEARCH_LVL_1. full_ms_params.prune_mesh_search = (q <= 20) ? 0 : 1; full_ms_params.mesh_search_mv_diff_threshold = 2; } av1_full_pixel_search(start_mv, &full_ms_params, step_param, cond_cost_list(cpi, cost_list), &best_mv.as_fullmv, &best_mv_stats, NULL); if (force_integer_mv == 1) { // Only do full search on the entire block. const int mv_row = best_mv.as_mv.row; const int mv_col = best_mv.as_mv.col; best_mv.as_mv.row = GET_MV_SUBPEL(mv_row); best_mv.as_mv.col = GET_MV_SUBPEL(mv_col); const int mv_offset = mv_row * y_stride + mv_col; error = cpi->ppi->fn_ptr[block_size].vf( ref_frame->y_buffer + y_offset + mv_offset, y_stride, frame_to_filter->y_buffer + y_offset, y_stride, &sse); block_mse = DIVIDE_AND_ROUND(error, mb_pels); block_mv = best_mv.as_mv; } else { // Do fractional search on the entire block and all sub-blocks. av1_make_default_subpel_ms_params(&ms_params, cpi, mb, block_size, &baseline_mv, cost_list); ms_params.forced_stop = EIGHTH_PEL; ms_params.var_params.subpel_search_type = subpel_search_type; // Since we are merely refining the result from full pixel search, we don't // need regularization for subpel search ms_params.mv_cost_params.mv_cost_type = MV_COST_NONE; best_mv_stats.err_cost = 0; MV subpel_start_mv = get_mv_from_fullmv(&best_mv.as_fullmv); assert(av1_is_subpelmv_in_range(&ms_params.mv_limits, subpel_start_mv)); error = cpi->mv_search_params.find_fractional_mv_step( &mb->e_mbd, &cpi->common, &ms_params, subpel_start_mv, &best_mv_stats, &best_mv.as_mv, &distortion, &sse, NULL); block_mse = DIVIDE_AND_ROUND(error, mb_pels); block_mv = best_mv.as_mv; *ref_mv = best_mv.as_mv; if (allow_me_for_sub_blks) { // On 4 sub-blocks. const BLOCK_SIZE subblock_size = av1_ss_size_lookup[block_size][1][1]; const int subblock_height = block_size_high[subblock_size]; const int subblock_width = block_size_wide[subblock_size]; const int subblock_pels = subblock_height * subblock_width; start_mv = get_fullmv_from_mv(ref_mv); int subblock_idx = 0; for (int i = 0; i < mb_height; i += subblock_height) { for (int j = 0; j < mb_width; j += subblock_width) { const int offset = i * y_stride + j; mb->plane[0].src.buf = frame_to_filter->y_buffer + y_offset + offset; mbd->plane[0].pre[0].buf = ref_frame->y_buffer + y_offset + offset; av1_make_default_fullpel_ms_params( &full_ms_params, cpi, mb, subblock_size, &baseline_mv, start_mv, search_site_cfg, search_method, /*fine_search_interval=*/0); full_ms_params.run_mesh_search = 1; full_ms_params.mv_cost_params.mv_cost_type = mv_cost_type; if (cpi->sf.mv_sf.prune_mesh_search == PRUNE_MESH_SEARCH_LVL_1) { // Enable prune_mesh_search based on q for PRUNE_MESH_SEARCH_LVL_1. full_ms_params.prune_mesh_search = (q <= 20) ? 0 : 1; full_ms_params.mesh_search_mv_diff_threshold = 2; } av1_full_pixel_search(start_mv, &full_ms_params, step_param, cond_cost_list(cpi, cost_list), &best_mv.as_fullmv, &best_mv_stats, NULL); av1_make_default_subpel_ms_params(&ms_params, cpi, mb, subblock_size, &baseline_mv, cost_list); ms_params.forced_stop = EIGHTH_PEL; ms_params.var_params.subpel_search_type = subpel_search_type; // Since we are merely refining the result from full pixel search, we // don't need regularization for subpel search ms_params.mv_cost_params.mv_cost_type = MV_COST_NONE; best_mv_stats.err_cost = 0; subpel_start_mv = get_mv_from_fullmv(&best_mv.as_fullmv); assert( av1_is_subpelmv_in_range(&ms_params.mv_limits, subpel_start_mv)); error = cpi->mv_search_params.find_fractional_mv_step( &mb->e_mbd, &cpi->common, &ms_params, subpel_start_mv, &best_mv_stats, &best_mv.as_mv, &distortion, &sse, NULL); subblock_mses[subblock_idx] = DIVIDE_AND_ROUND(error, subblock_pels); subblock_mvs[subblock_idx] = best_mv.as_mv; ++subblock_idx; } } } } // Restore input state. mb->plane[0].src = ori_src_buf; mbd->plane[0].pre[0] = ori_pre_buf; // Make partition decision. if (allow_me_for_sub_blks) { tf_determine_block_partition(block_mv, block_mse, subblock_mvs, subblock_mses); } else { // Copy 32X32 block mv and mse values to sub blocks for (int i = 0; i < 4; ++i) { subblock_mvs[i] = block_mv; subblock_mses[i] = block_mse; } } // Do not pass down the reference motion vector if error is too large. const int thresh = (min_frame_size >= 720) ? 12 : 3; if (block_mse > (thresh << (mbd->bd - 8))) { *ref_mv = kZeroMv; } } /*!\cond */ // Determines whether to split the entire block to 4 sub-blocks for filtering. // In particular, this decision is made based on the comparison between the // motion search error of the entire block and the errors of all sub-blocks. // Inputs: // block_mv: Motion vector for the entire block (ONLY as reference). // block_mse: Motion search error (MSE) for the entire block (ONLY as // reference). // subblock_mvs: Pointer to the motion vectors for 4 sub-blocks (will be // modified based on the partition decision). // subblock_mses: Pointer to the search errors (MSE) for 4 sub-blocks (will // be modified based on the partition decision). // Returns: // Nothing will be returned. Results are saved in `subblock_mvs` and // `subblock_mses`. static void tf_determine_block_partition(const MV block_mv, const int block_mse, MV *subblock_mvs, int *subblock_mses) { int min_subblock_mse = INT_MAX; int max_subblock_mse = INT_MIN; int64_t sum_subblock_mse = 0; for (int i = 0; i < 4; ++i) { sum_subblock_mse += subblock_mses[i]; min_subblock_mse = AOMMIN(min_subblock_mse, subblock_mses[i]); max_subblock_mse = AOMMAX(max_subblock_mse, subblock_mses[i]); } // TODO(any): The following magic numbers may be tuned to improve the // performance OR find a way to get rid of these magic numbers. if (((block_mse * 15 < sum_subblock_mse * 4) && max_subblock_mse - min_subblock_mse < 48) || ((block_mse * 14 < sum_subblock_mse * 4) && max_subblock_mse - min_subblock_mse < 24)) { // No split. for (int i = 0; i < 4; ++i) { subblock_mvs[i] = block_mv; subblock_mses[i] = block_mse; } } } // Helper function to determine whether a frame is encoded with high bit-depth. static inline int is_frame_high_bitdepth(const YV12_BUFFER_CONFIG *frame) { return (frame->flags & YV12_FLAG_HIGHBITDEPTH) ? 1 : 0; } /*!\endcond */ /*!\brief Builds predictor for blocks in temporal filtering. This is the * second step for temporal filtering, which is to construct predictions from * all reference frames INCLUDING the frame to be filtered itself. These * predictors are built based on the motion search results (motion vector is * set as 0 for the frame to be filtered), and will be futher used for * weighted averaging. * * \ingroup src_frame_proc * \param[in] ref_frame Pointer to the reference frame (or the frame * to be filtered) * \param[in] mbd Pointer to the block for filtering. Besides * containing the subsampling information of all * planes, this field also gives the searched * motion vector for the entire block, i.e., * `mbd->mi[0]->mv[0]`. This vector should be 0 * if the `ref_frame` itself is the frame to be * filtered. * \param[in] block_size Size of the block * \param[in] mb_row Row index of the block in the frame * \param[in] mb_col Column index of the block in the frame * \param[in] num_planes Number of planes in the frame * \param[in] scale Scaling factor * \param[in] subblock_mvs The motion vectors for each sub-block (row-major * order) * \param[out] pred Pointer to the predictor to be built * * \remark Nothing returned, But the contents of `pred` will be modified */ static void tf_build_predictor(const YV12_BUFFER_CONFIG *ref_frame, const MACROBLOCKD *mbd, const BLOCK_SIZE block_size, const int mb_row, const int mb_col, const int num_planes, const struct scale_factors *scale, const MV *subblock_mvs, uint8_t *pred) { // Information of the entire block. const int mb_height = block_size_high[block_size]; // Height. const int mb_width = block_size_wide[block_size]; // Width. const int mb_y = mb_height * mb_row; // Y-coord (Top-left). const int mb_x = mb_width * mb_col; // X-coord (Top-left). const int bit_depth = mbd->bd; // Bit depth. const int is_intrabc = 0; // Is intra-copied? const int is_high_bitdepth = is_frame_high_bitdepth(ref_frame); // Default interpolation filters. const int_interpfilters interp_filters = av1_broadcast_interp_filter(MULTITAP_SHARP2); // Handle Y-plane, U-plane and V-plane (if needed) in sequence. int plane_offset = 0; for (int plane = 0; plane < num_planes; ++plane) { const int subsampling_y = mbd->plane[plane].subsampling_y; const int subsampling_x = mbd->plane[plane].subsampling_x; // Information of each sub-block in current plane. const int plane_h = mb_height >> subsampling_y; // Plane height. const int plane_w = mb_width >> subsampling_x; // Plane width. const int plane_y = mb_y >> subsampling_y; // Y-coord (Top-left). const int plane_x = mb_x >> subsampling_x; // X-coord (Top-left). const int h = plane_h >> 1; // Sub-block height. const int w = plane_w >> 1; // Sub-block width. const int is_y_plane = (plane == 0); // Is Y-plane? const struct buf_2d ref_buf = { NULL, ref_frame->buffers[plane], ref_frame->widths[is_y_plane ? 0 : 1], ref_frame->heights[is_y_plane ? 0 : 1], ref_frame->strides[is_y_plane ? 0 : 1] }; // Handle each subblock. int subblock_idx = 0; for (int i = 0; i < plane_h; i += h) { for (int j = 0; j < plane_w; j += w) { // Choose proper motion vector. const MV mv = subblock_mvs[subblock_idx++]; assert(mv.row >= INT16_MIN && mv.row <= INT16_MAX && mv.col >= INT16_MIN && mv.col <= INT16_MAX); const int y = plane_y + i; const int x = plane_x + j; // Build predictior for each sub-block on current plane. InterPredParams inter_pred_params; av1_init_inter_params(&inter_pred_params, w, h, y, x, subsampling_x, subsampling_y, bit_depth, is_high_bitdepth, is_intrabc, scale, &ref_buf, interp_filters); inter_pred_params.conv_params = get_conv_params(0, plane, bit_depth); av1_enc_build_one_inter_predictor(&pred[plane_offset + i * plane_w + j], plane_w, &mv, &inter_pred_params); } } plane_offset += plane_h * plane_w; } } /*!\cond */ // Computes temporal filter weights and accumulators for the frame to be // filtered. More concretely, the filter weights for all pixels are the same. // Inputs: // mbd: Pointer to the block for filtering, which is ONLY used to get // subsampling information of all planes as well as the bit-depth. // block_size: Size of the block. // num_planes: Number of planes in the frame. // pred: Pointer to the well-built predictors. // accum: Pointer to the pixel-wise accumulator for filtering. // count: Pointer to the pixel-wise counter fot filtering. // Returns: // Nothing will be returned. But the content to which `accum` and `pred` // point will be modified. static void tf_apply_temporal_filter_self(const YV12_BUFFER_CONFIG *ref_frame, const MACROBLOCKD *mbd, const BLOCK_SIZE block_size, const int mb_row, const int mb_col, const int num_planes, uint32_t *accum, uint16_t *count) { // Block information. const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; const int is_high_bitdepth = is_cur_buf_hbd(mbd); int plane_offset = 0; for (int plane = 0; plane < num_planes; ++plane) { const int subsampling_y = mbd->plane[plane].subsampling_y; const int subsampling_x = mbd->plane[plane].subsampling_x; const int h = mb_height >> subsampling_y; // Plane height. const int w = mb_width >> subsampling_x; // Plane width. const int frame_stride = ref_frame->strides[plane == AOM_PLANE_Y ? 0 : 1]; const uint8_t *buf8 = ref_frame->buffers[plane]; const uint16_t *buf16 = CONVERT_TO_SHORTPTR(buf8); const int frame_offset = mb_row * h * frame_stride + mb_col * w; int pred_idx = 0; int pixel_idx = 0; for (int i = 0; i < h; ++i) { for (int j = 0; j < w; ++j) { const int idx = plane_offset + pred_idx; // Index with plane shift. const int pred_value = is_high_bitdepth ? buf16[frame_offset + pixel_idx] : buf8[frame_offset + pixel_idx]; accum[idx] += TF_WEIGHT_SCALE * pred_value; count[idx] += TF_WEIGHT_SCALE; ++pred_idx; ++pixel_idx; } pixel_idx += (frame_stride - w); } plane_offset += h * w; } } // Function to compute pixel-wise squared difference between two buffers. // Inputs: // ref: Pointer to reference buffer. // ref_offset: Start position of reference buffer for computation. // ref_stride: Stride for reference buffer. // tgt: Pointer to target buffer. // tgt_offset: Start position of target buffer for computation. // tgt_stride: Stride for target buffer. // height: Height of block for computation. // width: Width of block for computation. // is_high_bitdepth: Whether the two buffers point to high bit-depth frames. // square_diff: Pointer to save the squared differces. // Returns: // Nothing will be returned. But the content to which `square_diff` points // will be modified. static inline void compute_square_diff(const uint8_t *ref, const int ref_offset, const int ref_stride, const uint8_t *tgt, const int tgt_offset, const int tgt_stride, const int height, const int width, const int is_high_bitdepth, uint32_t *square_diff) { const uint16_t *ref16 = CONVERT_TO_SHORTPTR(ref); const uint16_t *tgt16 = CONVERT_TO_SHORTPTR(tgt); int ref_idx = 0; int tgt_idx = 0; int idx = 0; for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { const uint16_t ref_value = is_high_bitdepth ? ref16[ref_offset + ref_idx] : ref[ref_offset + ref_idx]; const uint16_t tgt_value = is_high_bitdepth ? tgt16[tgt_offset + tgt_idx] : tgt[tgt_offset + tgt_idx]; const uint32_t diff = (ref_value > tgt_value) ? (ref_value - tgt_value) : (tgt_value - ref_value); square_diff[idx] = diff * diff; ++ref_idx; ++tgt_idx; ++idx; } ref_idx += (ref_stride - width); tgt_idx += (tgt_stride - width); } } // Function to accumulate pixel-wise squared difference between two luma buffers // to be consumed while filtering the chroma planes. // Inputs: // square_diff: Pointer to squared differences from luma plane. // luma_sse_sum: Pointer to save the sum of luma squared differences. // block_height: Height of block for computation. // block_width: Width of block for computation. // ss_x_shift: Chroma subsampling shift in 'X' direction // ss_y_shift: Chroma subsampling shift in 'Y' direction // Returns: // Nothing will be returned. But the content to which `luma_sse_sum` points // will be modified. static void compute_luma_sq_error_sum(uint32_t *square_diff, uint32_t *luma_sse_sum, int block_height, int block_width, int ss_x_shift, int ss_y_shift) { for (int i = 0; i < block_height; ++i) { for (int j = 0; j < block_width; ++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 = block_width << ss_x_shift; // Width of Y-plane. luma_sse_sum[i * block_width + j] += square_diff[yy * ww + xx]; } } } } } /*!\endcond */ /*!\brief Applies temporal filtering. NOTE that there are various optimised * versions of this function called where the appropriate instruction set is * supported. * * \ingroup src_frame_proc * \param[in] frame_to_filter Pointer to the frame to be filtered, which is * used as reference to compute squared * difference from the predictor. * \param[in] mbd Pointer to the block for filtering, ONLY used * to get subsampling information for the planes * \param[in] block_size Size of the block * \param[in] mb_row Row index of the block in the frame * \param[in] mb_col Column index of the block in the frame * \param[in] num_planes Number of planes in the frame * \param[in] noise_levels Estimated noise levels for each plane * in the frame (Y,U,V) * \param[in] subblock_mvs Pointer to the motion vectors for 4 sub-blocks * \param[in] subblock_mses Pointer to the search errors (MSE) for 4 * sub-blocks * \param[in] q_factor Quantization factor. This is actually the `q` * defined in libaom, converted from `qindex` * \param[in] filter_strength Filtering strength. This value lies in range * [0, 6] where 6 is the maximum strength. * \param[in] tf_wgt_calc_lvl Controls the weight calculation method during * temporal filtering * \param[out] pred Pointer to the well-built predictors * \param[out] accum Pointer to the pixel-wise accumulator for * filtering * \param[out] count Pointer to the pixel-wise counter for * filtering * * \remark Nothing returned, But the contents of `accum`, `pred` and 'count' * will be modified */ void av1_apply_temporal_filter_c( 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 *pred, uint32_t *accum, uint16_t *count) { // Block information. const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; const int mb_pels = mb_height * mb_width; const int is_high_bitdepth = is_frame_high_bitdepth(frame_to_filter); const uint16_t *pred16 = CONVERT_TO_SHORTPTR(pred); // 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; // Decay factors for non-local mean approach. double decay_factor[MAX_MB_PLANE] = { 0 }; // 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); for (int plane = 0; plane < num_planes; plane++) { // Larger noise -> larger filtering weight. const double n_decay = 0.5 + log(2 * noise_levels[plane] + 5.0); decay_factor[plane] = 1 / (n_decay * q_decay * s_decay); } double d_factor[4] = { 0 }; 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); } // Allocate memory for pixel-wise squared differences. They, // regardless of the subsampling, are assigned with memory of size `mb_pels`. uint32_t *square_diff = aom_memalign(16, mb_pels * sizeof(uint32_t)); if (!square_diff) { aom_internal_error(mbd->error_info, AOM_CODEC_MEM_ERROR, "Error allocating temporal filter data"); } memset(square_diff, 0, mb_pels * sizeof(square_diff[0])); // Allocate memory for accumulated luma squared error. This value will be // consumed while filtering the chroma planes. uint32_t *luma_sse_sum = aom_memalign(32, mb_pels * sizeof(uint32_t)); if (!luma_sse_sum) { aom_free(square_diff); aom_internal_error(mbd->error_info, AOM_CODEC_MEM_ERROR, "Error allocating temporal filter data"); } memset(luma_sse_sum, 0, mb_pels * sizeof(luma_sse_sum[0])); // Get window size for pixel-wise filtering. assert(TF_WINDOW_LENGTH % 2 == 1); const int half_window = TF_WINDOW_LENGTH >> 1; // Handle planes in sequence. int plane_offset = 0; for (int plane = 0; plane < num_planes; ++plane) { // Locate pixel on reference frame. const int subsampling_y = mbd->plane[plane].subsampling_y; const int subsampling_x = mbd->plane[plane].subsampling_x; const int h = mb_height >> subsampling_y; // Plane height. const int w = mb_width >> subsampling_x; // Plane width. const int frame_stride = frame_to_filter->strides[plane == AOM_PLANE_Y ? 0 : 1]; const int frame_offset = mb_row * h * frame_stride + mb_col * w; const uint8_t *ref = frame_to_filter->buffers[plane]; const int ss_y_shift = subsampling_y - mbd->plane[AOM_PLANE_Y].subsampling_y; const int ss_x_shift = subsampling_x - mbd->plane[AOM_PLANE_Y].subsampling_x; 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; // 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) compute_luma_sq_error_sum(square_diff, luma_sse_sum, h, w, ss_x_shift, ss_y_shift); compute_square_diff(ref, frame_offset, frame_stride, pred, plane_offset, w, h, w, is_high_bitdepth, square_diff); // Perform filtering. int pred_idx = 0; for (int i = 0; i < h; ++i) { for (int j = 0; j < w; ++j) { // non-local mean approach uint64_t sum_square_diff = 0; for (int wi = -half_window; wi <= half_window; ++wi) { for (int wj = -half_window; wj <= half_window; ++wj) { const int y = CLIP(i + wi, 0, h - 1); // Y-coord on current plane. const int x = CLIP(j + wj, 0, w - 1); // X-coord on current plane. sum_square_diff += square_diff[y * w + x]; } } sum_square_diff += luma_sse_sum[i * w + j]; // Scale down the difference for high bit depth input. if (mbd->bd > 8) sum_square_diff >>= ((mbd->bd - 8) * 2); // Combine window error and block error, and normalize it. const double window_error = sum_square_diff * inv_num_ref_pixels; const int subblock_idx = (i >= h / 2) * 2 + (j >= w / 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[plane]; scaled_error = AOMMIN(scaled_error, 7); int weight; if (tf_wgt_calc_lvl == 0) { weight = (int)(exp(-scaled_error) * TF_WEIGHT_SCALE); } else { const float fweight = approx_exp((float)-scaled_error) * TF_WEIGHT_SCALE; weight = iroundpf(fweight); } const int idx = plane_offset + pred_idx; // Index with plane shift. const int pred_value = is_high_bitdepth ? pred16[idx] : pred[idx]; accum[idx] += weight * pred_value; count[idx] += weight; ++pred_idx; } } plane_offset += h * w; } aom_free(square_diff); aom_free(luma_sse_sum); } #if CONFIG_AV1_HIGHBITDEPTH // Calls High bit-depth temporal filter void av1_highbd_apply_temporal_filter_c( 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 *pred, uint32_t *accum, uint16_t *count) { av1_apply_temporal_filter_c(frame_to_filter, mbd, block_size, mb_row, mb_col, num_planes, noise_levels, subblock_mvs, subblock_mses, q_factor, filter_strength, tf_wgt_calc_lvl, pred, accum, count); } #endif // CONFIG_AV1_HIGHBITDEPTH /*!\brief Normalizes the accumulated filtering result to produce the filtered * frame * * \ingroup src_frame_proc * \param[in] mbd Pointer to the block for filtering, which is * ONLY used to get subsampling information for * all the planes * \param[in] block_size Size of the block * \param[in] mb_row Row index of the block in the frame * \param[in] mb_col Column index of the block in the frame * \param[in] num_planes Number of planes in the frame * \param[in] accum Pointer to the pre-computed accumulator * \param[in] count Pointer to the pre-computed count * \param[out] result_buffer Pointer to result buffer * * \remark Nothing returned, but the content to which `result_buffer` pointer * will be modified */ static void tf_normalize_filtered_frame( const MACROBLOCKD *mbd, const BLOCK_SIZE block_size, const int mb_row, const int mb_col, const int num_planes, const uint32_t *accum, const uint16_t *count, YV12_BUFFER_CONFIG *result_buffer) { // Block information. const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; const int is_high_bitdepth = is_frame_high_bitdepth(result_buffer); int plane_offset = 0; for (int plane = 0; plane < num_planes; ++plane) { const int plane_h = mb_height >> mbd->plane[plane].subsampling_y; const int plane_w = mb_width >> mbd->plane[plane].subsampling_x; const int frame_stride = result_buffer->strides[plane == 0 ? 0 : 1]; const int frame_offset = mb_row * plane_h * frame_stride + mb_col * plane_w; uint8_t *const buf = result_buffer->buffers[plane]; uint16_t *const buf16 = CONVERT_TO_SHORTPTR(buf); int plane_idx = 0; // Pixel index on current plane (block-base). int frame_idx = frame_offset; // Pixel index on the entire frame. for (int i = 0; i < plane_h; ++i) { for (int j = 0; j < plane_w; ++j) { const int idx = plane_idx + plane_offset; const uint16_t rounding = count[idx] >> 1; if (is_high_bitdepth) { buf16[frame_idx] = (uint16_t)OD_DIVU(accum[idx] + rounding, count[idx]); } else { buf[frame_idx] = (uint8_t)OD_DIVU(accum[idx] + rounding, count[idx]); } ++plane_idx; ++frame_idx; } frame_idx += (frame_stride - plane_w); } plane_offset += plane_h * plane_w; } } void av1_tf_do_filtering_row(AV1_COMP *cpi, ThreadData *td, int mb_row) { TemporalFilterCtx *tf_ctx = &cpi->tf_ctx; YV12_BUFFER_CONFIG **frames = tf_ctx->frames; const int num_frames = tf_ctx->num_frames; const int filter_frame_idx = tf_ctx->filter_frame_idx; const int compute_frame_diff = tf_ctx->compute_frame_diff; const struct scale_factors *scale = &tf_ctx->sf; const double *noise_levels = tf_ctx->noise_levels; const int num_pels = tf_ctx->num_pels; const int q_factor = tf_ctx->q_factor; const BLOCK_SIZE block_size = TF_BLOCK_SIZE; const YV12_BUFFER_CONFIG *const frame_to_filter = frames[filter_frame_idx]; MACROBLOCK *const mb = &td->mb; MACROBLOCKD *const mbd = &mb->e_mbd; TemporalFilterData *const tf_data = &td->tf_data; const int mb_height = block_size_high[block_size]; const int mb_width = block_size_wide[block_size]; const int mi_h = mi_size_high_log2[block_size]; const int mi_w = mi_size_wide_log2[block_size]; const int num_planes = av1_num_planes(&cpi->common); const int weight_calc_level_in_tf = cpi->sf.hl_sf.weight_calc_level_in_tf; uint32_t *accum = tf_data->accum; uint16_t *count = tf_data->count; uint8_t *pred = tf_data->pred; // Factor to control the filering strength. const int filter_strength = cpi->oxcf.algo_cfg.arnr_strength; // Do filtering. FRAME_DIFF *diff = &td->tf_data.diff; av1_set_mv_row_limits(&cpi->common.mi_params, &mb->mv_limits, (mb_row << mi_h), (mb_height >> MI_SIZE_LOG2), cpi->oxcf.border_in_pixels); for (int mb_col = 0; mb_col < tf_ctx->mb_cols; mb_col++) { av1_set_mv_col_limits(&cpi->common.mi_params, &mb->mv_limits, (mb_col << mi_w), (mb_width >> MI_SIZE_LOG2), cpi->oxcf.border_in_pixels); memset(accum, 0, num_pels * sizeof(accum[0])); memset(count, 0, num_pels * sizeof(count[0])); MV ref_mv = kZeroMv; // Reference motion vector passed down along frames. // Perform temporal filtering frame by frame. // Decide whether to perform motion search at 16x16 sub-block level or not // based on 4x4 sub-blocks source variance. Allow motion search for split // partition only if the difference between max and min source variance of // 4x4 blocks is greater than a threshold (which is derived empirically). bool allow_me_for_sub_blks = true; if (cpi->sf.hl_sf.allow_sub_blk_me_in_tf) { const int is_hbd = is_frame_high_bitdepth(frame_to_filter); // Initialize minimum variance to a large value and maximum variance to 0. double blk_4x4_var_min = DBL_MAX; double blk_4x4_var_max = 0; get_log_var_4x4sub_blk(cpi, frame_to_filter, mb_row, mb_col, TF_BLOCK_SIZE, &blk_4x4_var_min, &blk_4x4_var_max, is_hbd); // TODO(sanampudi.venkatarao@ittiam.com): Experiment and adjust the // threshold for high bit depth. if ((blk_4x4_var_max - blk_4x4_var_min) <= 4.0) allow_me_for_sub_blks = false; } for (int frame = 0; frame < num_frames; frame++) { if (frames[frame] == NULL) continue; // Motion search. MV subblock_mvs[4] = { kZeroMv, kZeroMv, kZeroMv, kZeroMv }; int subblock_mses[4] = { INT_MAX, INT_MAX, INT_MAX, INT_MAX }; if (frame == filter_frame_idx) { // Frame to be filtered. // Change ref_mv sign for following frames. ref_mv.row *= -1; ref_mv.col *= -1; } else { // Other reference frames. tf_motion_search(cpi, mb, frame_to_filter, frames[frame], block_size, mb_row, mb_col, &ref_mv, allow_me_for_sub_blks, subblock_mvs, subblock_mses); } // Perform weighted averaging. if (frame == filter_frame_idx) { // Frame to be filtered. tf_apply_temporal_filter_self(frames[frame], mbd, block_size, mb_row, mb_col, num_planes, accum, count); } else { // Other reference frames. tf_build_predictor(frames[frame], mbd, block_size, mb_row, mb_col, num_planes, scale, subblock_mvs, pred); // All variants of av1_apply_temporal_filter() contain floating point // operations. Hence, clear the system state. // TODO(any): avx2/sse2 version should be changed to align with C // function before using. In particular, current avx2/sse2 function // only supports 32x32 block size and 5x5 filtering window. if (is_frame_high_bitdepth(frame_to_filter)) { // for high bit-depth #if CONFIG_AV1_HIGHBITDEPTH if (TF_BLOCK_SIZE == BLOCK_32X32 && TF_WINDOW_LENGTH == 5) { av1_highbd_apply_temporal_filter( frame_to_filter, mbd, block_size, mb_row, mb_col, num_planes, noise_levels, subblock_mvs, subblock_mses, q_factor, filter_strength, weight_calc_level_in_tf, pred, accum, count); } else { #endif // CONFIG_AV1_HIGHBITDEPTH av1_apply_temporal_filter_c( frame_to_filter, mbd, block_size, mb_row, mb_col, num_planes, noise_levels, subblock_mvs, subblock_mses, q_factor, filter_strength, weight_calc_level_in_tf, pred, accum, count); #if CONFIG_AV1_HIGHBITDEPTH } #endif // CONFIG_AV1_HIGHBITDEPTH } else { // for 8-bit if (TF_BLOCK_SIZE == BLOCK_32X32 && TF_WINDOW_LENGTH == 5) { av1_apply_temporal_filter( frame_to_filter, mbd, block_size, mb_row, mb_col, num_planes, noise_levels, subblock_mvs, subblock_mses, q_factor, filter_strength, weight_calc_level_in_tf, pred, accum, count); } else { av1_apply_temporal_filter_c( frame_to_filter, mbd, block_size, mb_row, mb_col, num_planes, noise_levels, subblock_mvs, subblock_mses, q_factor, filter_strength, weight_calc_level_in_tf, pred, accum, count); } } } } tf_normalize_filtered_frame(mbd, block_size, mb_row, mb_col, num_planes, accum, count, tf_ctx->output_frame); if (compute_frame_diff) { const int y_height = mb_height >> mbd->plane[0].subsampling_y; const int y_width = mb_width >> mbd->plane[0].subsampling_x; const int source_y_stride = frame_to_filter->y_stride; const int filter_y_stride = tf_ctx->output_frame->y_stride; const int source_offset = mb_row * y_height * source_y_stride + mb_col * y_width; const int filter_offset = mb_row * y_height * filter_y_stride + mb_col * y_width; unsigned int sse = 0; cpi->ppi->fn_ptr[block_size].vf( frame_to_filter->y_buffer + source_offset, source_y_stride, tf_ctx->output_frame->y_buffer + filter_offset, filter_y_stride, &sse); diff->sum += sse; diff->sse += sse * (int64_t)sse; } } } /*!\brief Does temporal filter for a given frame. * * \ingroup src_frame_proc * \param[in] cpi Top level encoder instance structure * * \remark Nothing will be returned, but the contents of td->diff will be modified. */ static void tf_do_filtering(AV1_COMP *cpi) { // Basic information. ThreadData *td = &cpi->td; TemporalFilterCtx *tf_ctx = &cpi->tf_ctx; const struct scale_factors *scale = &tf_ctx->sf; const int num_planes = av1_num_planes(&cpi->common); assert(num_planes >= 1 && num_planes <= MAX_MB_PLANE); MACROBLOCKD *mbd = &td->mb.e_mbd; uint8_t *input_buffer[MAX_MB_PLANE]; MB_MODE_INFO **input_mb_mode_info; tf_save_state(mbd, &input_mb_mode_info, input_buffer, num_planes); tf_setup_macroblockd(mbd, &td->tf_data, scale); // Perform temporal filtering for each row. for (int mb_row = 0; mb_row < tf_ctx->mb_rows; mb_row++) av1_tf_do_filtering_row(cpi, td, mb_row); tf_restore_state(mbd, input_mb_mode_info, input_buffer, num_planes); } /*!\brief Setups the frame buffer for temporal filtering. This fuction * determines how many frames will be used for temporal filtering and then * groups them into a buffer. This function will also estimate the noise level * of the to-filter frame. * * \ingroup src_frame_proc * \param[in] cpi Top level encoder instance structure * \param[in] filter_frame_lookahead_idx The index of the to-filter frame * in the lookahead buffer cpi->lookahead * \param[in] gf_frame_index GOP index * * \remark Nothing will be returned. But the fields `frames`, `num_frames`, * `filter_frame_idx` and `noise_levels` will be updated in cpi->tf_ctx. */ static void tf_setup_filtering_buffer(AV1_COMP *cpi, int filter_frame_lookahead_idx, int gf_frame_index) { const GF_GROUP *gf_group = &cpi->ppi->gf_group; const FRAME_UPDATE_TYPE update_type = gf_group->update_type[gf_frame_index]; const FRAME_TYPE frame_type = gf_group->frame_type[gf_frame_index]; const int is_forward_keyframe = av1_gop_check_forward_keyframe(gf_group, gf_frame_index); TemporalFilterCtx *tf_ctx = &cpi->tf_ctx; YV12_BUFFER_CONFIG **frames = tf_ctx->frames; // Number of frames used for filtering. Set `arnr_max_frames` as 1 to disable // temporal filtering. int num_frames = AOMMAX(cpi->oxcf.algo_cfg.arnr_max_frames, 1); int num_before = 0; // Number of filtering frames before the to-filter frame. int num_after = 0; // Number of filtering frames after the to-filer frame. const int lookahead_depth = av1_lookahead_depth(cpi->ppi->lookahead, cpi->compressor_stage); // Temporal filtering should not go beyond key frames const int key_to_curframe = AOMMAX(cpi->rc.frames_since_key + filter_frame_lookahead_idx, 0); const int curframe_to_key = AOMMAX(cpi->rc.frames_to_key - filter_frame_lookahead_idx - 1, 0); // Number of buffered frames before the to-filter frame. int max_before = AOMMIN(filter_frame_lookahead_idx, key_to_curframe); // Number of buffered frames after the to-filter frame. int max_after = AOMMIN(lookahead_depth - filter_frame_lookahead_idx - 1, curframe_to_key); // Estimate noises for each plane. const struct lookahead_entry *to_filter_buf = av1_lookahead_peek( cpi->ppi->lookahead, filter_frame_lookahead_idx, cpi->compressor_stage); assert(to_filter_buf != NULL); const YV12_BUFFER_CONFIG *to_filter_frame = &to_filter_buf->img; const int num_planes = av1_num_planes(&cpi->common); double *noise_levels = tf_ctx->noise_levels; av1_estimate_noise_level(to_filter_frame, noise_levels, AOM_PLANE_Y, num_planes - 1, cpi->common.seq_params->bit_depth, NOISE_ESTIMATION_EDGE_THRESHOLD); // Get quantization factor. const int q = get_q(cpi); // Get correlation estimates from first-pass; const FIRSTPASS_STATS *stats = cpi->twopass_frame.stats_in - (cpi->rc.frames_since_key == 0); double accu_coeff0 = 1.0, accu_coeff1 = 1.0; for (int i = 1; i <= max_after; i++) { if (stats + filter_frame_lookahead_idx + i >= cpi->ppi->twopass.stats_buf_ctx->stats_in_end) { max_after = i - 1; break; } accu_coeff1 *= AOMMAX(stats[filter_frame_lookahead_idx + i].cor_coeff, 0.001); } if (max_after >= 1) { accu_coeff1 = pow(accu_coeff1, 1.0 / (double)max_after); } for (int i = 1; i <= max_before; i++) { if (stats + filter_frame_lookahead_idx - i + 1 <= cpi->ppi->twopass.stats_buf_ctx->stats_in_start) { max_before = i - 1; break; } accu_coeff0 *= AOMMAX(stats[filter_frame_lookahead_idx - i + 1].cor_coeff, 0.001); } if (max_before >= 1) { accu_coeff0 = pow(accu_coeff0, 1.0 / (double)max_before); } // Adjust number of filtering frames based on quantization factor. When the // quantization factor is small enough (lossless compression), we will not // change the number of frames for key frame filtering, which is to avoid // visual quality drop. int adjust_num = 6; const int adjust_num_frames_for_arf_filtering = cpi->sf.hl_sf.adjust_num_frames_for_arf_filtering; if (num_frames == 1) { // `arnr_max_frames = 1` is used to disable filtering. adjust_num = 0; } else if ((update_type == KF_UPDATE) && q <= 10) { adjust_num = 0; } else if (adjust_num_frames_for_arf_filtering > 0 && update_type != KF_UPDATE && (cpi->rc.frames_since_key > 0)) { // Since screen content detection happens after temporal filtering, // 'frames_since_key' check is added to ensure the sf is disabled for the // first alt-ref frame. // Adjust number of frames to be considered for filtering based on noise // level of the current frame. For low-noise frame, use more frames to // filter such that the filtered frame can provide better predictions for // subsequent frames and vice versa. const uint8_t av1_adjust_num_using_noise_lvl[2][3] = { { 6, 4, 2 }, { 4, 2, 0 } }; const uint8_t *adjust_num_frames = av1_adjust_num_using_noise_lvl[adjust_num_frames_for_arf_filtering - 1]; if (noise_levels[AOM_PLANE_Y] < 0.5) adjust_num = adjust_num_frames[0]; else if (noise_levels[AOM_PLANE_Y] < 1.0) adjust_num = adjust_num_frames[1]; else adjust_num = adjust_num_frames[2]; } num_frames = AOMMIN(num_frames + adjust_num, lookahead_depth); if (frame_type == KEY_FRAME) { num_before = AOMMIN(is_forward_keyframe ? num_frames / 2 : 0, max_before); num_after = AOMMIN(num_frames - 1, max_after); } else { int gfu_boost = av1_calc_arf_boost(&cpi->ppi->twopass, &cpi->twopass_frame, &cpi->ppi->p_rc, &cpi->frame_info, filter_frame_lookahead_idx, max_before, max_after, NULL, NULL, 0); num_frames = AOMMIN(num_frames, gfu_boost / 150); num_frames += !(num_frames & 1); // Make the number odd. // Only use 2 neighbours for the second ARF. if (update_type == INTNL_ARF_UPDATE) num_frames = AOMMIN(num_frames, 3); if (AOMMIN(max_after, max_before) >= num_frames / 2) { // just use half half num_before = num_frames / 2; num_after = num_frames / 2; } else { if (max_after < num_frames / 2) { num_after = max_after; num_before = AOMMIN(num_frames - 1 - num_after, max_before); } else { num_before = max_before; num_after = AOMMIN(num_frames - 1 - num_before, max_after); } // Adjust insymmetry based on frame-level correlation if (max_after > 0 && max_before > 0) { if (num_after < num_before) { const int insym = (int)(0.4 / AOMMAX(1 - accu_coeff1, 0.01)); num_before = AOMMIN(num_before, num_after + insym); } else { const int insym = (int)(0.4 / AOMMAX(1 - accu_coeff0, 0.01)); num_after = AOMMIN(num_after, num_before + insym); } } } } num_frames = num_before + 1 + num_after; // Setup the frame buffer. for (int frame = 0; frame < num_frames; ++frame) { const int lookahead_idx = frame - num_before + filter_frame_lookahead_idx; struct lookahead_entry *buf = av1_lookahead_peek( cpi->ppi->lookahead, lookahead_idx, cpi->compressor_stage); assert(buf != NULL); frames[frame] = &buf->img; } tf_ctx->num_frames = num_frames; tf_ctx->filter_frame_idx = num_before; assert(frames[tf_ctx->filter_frame_idx] == to_filter_frame); av1_setup_src_planes(&cpi->td.mb, &to_filter_buf->img, 0, 0, num_planes, cpi->common.seq_params->sb_size); av1_setup_block_planes(&cpi->td.mb.e_mbd, cpi->common.seq_params->subsampling_x, cpi->common.seq_params->subsampling_y, num_planes); } /*!\cond */ double av1_estimate_noise_from_single_plane_c(const uint8_t *src, int height, int width, int stride, int edge_thresh) { int64_t accum = 0; int count = 0; for (int i = 1; i < height - 1; ++i) { for (int j = 1; j < width - 1; ++j) { // Setup a small 3x3 matrix. const int center_idx = i * stride + j; int mat[3][3]; for (int ii = -1; ii <= 1; ++ii) { for (int jj = -1; jj <= 1; ++jj) { const int idx = center_idx + ii * stride + jj; mat[ii + 1][jj + 1] = src[idx]; } } // 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), 0); // Accumulate Laplacian. if (Ga < edge_thresh) { // Only count smooth pixels. 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]); accum += ROUND_POWER_OF_TWO(abs(v), 0); ++count; } } } // Return -1.0 (unreliable estimation) if there are too few smooth pixels. return (count < 16) ? -1.0 : (double)accum / (6 * count) * SQRT_PI_BY_2; } #if CONFIG_AV1_HIGHBITDEPTH double av1_highbd_estimate_noise_from_single_plane_c(const uint16_t *src16, int height, int width, const int stride, int bit_depth, int edge_thresh) { int64_t accum = 0; int count = 0; for (int i = 1; i < height - 1; ++i) { for (int j = 1; j < width - 1; ++j) { // Setup a small 3x3 matrix. const int center_idx = i * stride + j; int mat[3][3]; for (int ii = -1; ii <= 1; ++ii) { for (int jj = -1; jj <= 1; ++jj) { const int idx = center_idx + ii * stride + jj; mat[ii + 1][jj + 1] = src16[idx]; } } // 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), bit_depth - 8); // Accumulate Laplacian. if (Ga < edge_thresh) { // Only count smooth pixels. 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]); accum += ROUND_POWER_OF_TWO(abs(v), bit_depth - 8); ++count; } } } // Return -1.0 (unreliable estimation) if there are too few smooth pixels. return (count < 16) ? -1.0 : (double)accum / (6 * count) * SQRT_PI_BY_2; } #endif void av1_estimate_noise_level(const YV12_BUFFER_CONFIG *frame, double *noise_level, int plane_from, int plane_to, int bit_depth, int edge_thresh) { for (int plane = plane_from; plane <= plane_to; plane++) { const bool is_uv_plane = (plane != AOM_PLANE_Y); const int height = frame->crop_heights[is_uv_plane]; const int width = frame->crop_widths[is_uv_plane]; const int stride = frame->strides[is_uv_plane]; const uint8_t *src = frame->buffers[plane]; #if CONFIG_AV1_HIGHBITDEPTH const uint16_t *src16 = CONVERT_TO_SHORTPTR(src); const int is_high_bitdepth = is_frame_high_bitdepth(frame); if (is_high_bitdepth) { noise_level[plane] = av1_highbd_estimate_noise_from_single_plane( src16, height, width, stride, bit_depth, edge_thresh); } else { noise_level[plane] = av1_estimate_noise_from_single_plane( src, height, width, stride, edge_thresh); } #else (void)bit_depth; noise_level[plane] = av1_estimate_noise_from_single_plane( src, height, width, stride, edge_thresh); #endif } } // Initializes the members of TemporalFilterCtx // Inputs: // cpi: Top level encoder instance structure // check_show_existing: If 1, check whether the filtered frame is similar // to the original frame. // filter_frame_lookahead_idx: The index of the frame to be filtered in the // lookahead buffer cpi->lookahead. // Returns: // Nothing will be returned. But the contents of cpi->tf_ctx will be modified. static void init_tf_ctx(AV1_COMP *cpi, int filter_frame_lookahead_idx, int gf_frame_index, int compute_frame_diff, YV12_BUFFER_CONFIG *output_frame) { TemporalFilterCtx *tf_ctx = &cpi->tf_ctx; // Setup frame buffer for filtering. YV12_BUFFER_CONFIG **frames = tf_ctx->frames; tf_ctx->num_frames = 0; tf_ctx->filter_frame_idx = -1; tf_ctx->output_frame = output_frame; tf_ctx->compute_frame_diff = compute_frame_diff; tf_setup_filtering_buffer(cpi, filter_frame_lookahead_idx, gf_frame_index); assert(tf_ctx->num_frames > 0); assert(tf_ctx->filter_frame_idx < tf_ctx->num_frames); // Setup scaling factors. Scaling on each of the arnr frames is not // supported. // ARF is produced at the native frame size and resized when coded. struct scale_factors *sf = &tf_ctx->sf; av1_setup_scale_factors_for_frame( sf, frames[0]->y_crop_width, frames[0]->y_crop_height, frames[0]->y_crop_width, frames[0]->y_crop_height); // Initialize temporal filter parameters. MACROBLOCKD *mbd = &cpi->td.mb.e_mbd; const int filter_frame_idx = tf_ctx->filter_frame_idx; const YV12_BUFFER_CONFIG *const frame_to_filter = frames[filter_frame_idx]; const BLOCK_SIZE block_size = TF_BLOCK_SIZE; const int frame_height = frame_to_filter->y_crop_height; const int frame_width = frame_to_filter->y_crop_width; const int mb_width = block_size_wide[block_size]; const int mb_height = block_size_high[block_size]; const int mb_rows = get_num_blocks(frame_height, mb_height); const int mb_cols = get_num_blocks(frame_width, mb_width); const int mb_pels = mb_width * mb_height; const int is_highbitdepth = is_frame_high_bitdepth(frame_to_filter); const int num_planes = av1_num_planes(&cpi->common); int num_pels = 0; for (int i = 0; i < num_planes; i++) { const int subsampling_x = mbd->plane[i].subsampling_x; const int subsampling_y = mbd->plane[i].subsampling_y; num_pels += mb_pels >> (subsampling_x + subsampling_y); } tf_ctx->num_pels = num_pels; tf_ctx->mb_rows = mb_rows; tf_ctx->mb_cols = mb_cols; tf_ctx->is_highbitdepth = is_highbitdepth; tf_ctx->q_factor = get_q(cpi); } int av1_check_show_filtered_frame(const YV12_BUFFER_CONFIG *frame, const FRAME_DIFF *frame_diff, int q_index, aom_bit_depth_t bit_depth) { const int frame_height = frame->y_crop_height; const int frame_width = frame->y_crop_width; const int block_height = block_size_high[TF_BLOCK_SIZE]; const int block_width = block_size_wide[TF_BLOCK_SIZE]; const int mb_rows = get_num_blocks(frame_height, block_height); const int mb_cols = get_num_blocks(frame_width, block_width); const int num_mbs = AOMMAX(1, mb_rows * mb_cols); const float mean = (float)frame_diff->sum / num_mbs; const float std = (float)sqrt((float)frame_diff->sse / num_mbs - mean * mean); const int ac_q_step = av1_ac_quant_QTX(q_index, 0, bit_depth); const float threshold = 0.7f * ac_q_step * ac_q_step; if (mean < threshold && std < mean * 1.2) { return 1; } return 0; } void av1_temporal_filter(AV1_COMP *cpi, const int filter_frame_lookahead_idx, int gf_frame_index, FRAME_DIFF *frame_diff, YV12_BUFFER_CONFIG *output_frame) { MultiThreadInfo *const mt_info = &cpi->mt_info; // Basic informaton of the current frame. TemporalFilterCtx *tf_ctx = &cpi->tf_ctx; TemporalFilterData *tf_data = &cpi->td.tf_data; const int compute_frame_diff = frame_diff != NULL; // TODO(anyone): Currently, we enforce the filtering strength on internal // ARFs except the second ARF to be zero. We should investigate in which case // it is more beneficial to use non-zero strength filtering. // Only parallel level 0 frames go through temporal filtering. assert(cpi->ppi->gf_group.frame_parallel_level[gf_frame_index] == 0); // Initialize temporal filter context structure. init_tf_ctx(cpi, filter_frame_lookahead_idx, gf_frame_index, compute_frame_diff, output_frame); // Allocate and reset temporal filter buffers. const int is_highbitdepth = tf_ctx->is_highbitdepth; if (!tf_alloc_and_reset_data(tf_data, tf_ctx->num_pels, is_highbitdepth)) { aom_internal_error(cpi->common.error, AOM_CODEC_MEM_ERROR, "Error allocating temporal filter data"); } // Perform temporal filtering process. if (mt_info->num_workers > 1) av1_tf_do_filtering_mt(cpi); else tf_do_filtering(cpi); if (compute_frame_diff) { *frame_diff = tf_data->diff; } // Deallocate temporal filter buffers. tf_dealloc_data(tf_data, is_highbitdepth); } int av1_is_temporal_filter_on(const AV1EncoderConfig *oxcf) { return oxcf->algo_cfg.arnr_max_frames > 0 && oxcf->gf_cfg.lag_in_frames > 1; } bool av1_tf_info_alloc(TEMPORAL_FILTER_INFO *tf_info, const AV1_COMP *cpi) { const AV1EncoderConfig *oxcf = &cpi->oxcf; tf_info->is_temporal_filter_on = av1_is_temporal_filter_on(oxcf); if (tf_info->is_temporal_filter_on == 0) return true; const AV1_COMMON *cm = &cpi->common; const SequenceHeader *const seq_params = cm->seq_params; for (int i = 0; i < TF_INFO_BUF_COUNT; ++i) { if (aom_realloc_frame_buffer( &tf_info->tf_buf[i], oxcf->frm_dim_cfg.width, oxcf->frm_dim_cfg.height, seq_params->subsampling_x, seq_params->subsampling_y, seq_params->use_highbitdepth, cpi->oxcf.border_in_pixels, cm->features.byte_alignment, NULL, NULL, NULL, cpi->alloc_pyramid, 0)) { return false; } } return true; } void av1_tf_info_free(TEMPORAL_FILTER_INFO *tf_info) { if (tf_info->is_temporal_filter_on == 0) return; for (int i = 0; i < TF_INFO_BUF_COUNT; ++i) { aom_free_frame_buffer(&tf_info->tf_buf[i]); } aom_free_frame_buffer(&tf_info->tf_buf_second_arf); } void av1_tf_info_reset(TEMPORAL_FILTER_INFO *tf_info) { av1_zero(tf_info->tf_buf_valid); av1_zero(tf_info->tf_buf_gf_index); av1_zero(tf_info->tf_buf_display_index_offset); } void av1_tf_info_filtering(TEMPORAL_FILTER_INFO *tf_info, AV1_COMP *cpi, const GF_GROUP *gf_group) { if (tf_info->is_temporal_filter_on == 0) return; const AV1_COMMON *const cm = &cpi->common; for (int gf_index = 0; gf_index < gf_group->size; ++gf_index) { int update_type = gf_group->update_type[gf_index]; if (update_type == KF_UPDATE || update_type == ARF_UPDATE) { int buf_idx = gf_group->frame_type[gf_index] == INTER_FRAME; int lookahead_idx = gf_group->arf_src_offset[gf_index] + gf_group->cur_frame_idx[gf_index]; // This function is designed to be called multiple times after // av1_tf_info_reset(). It will only generate the filtered frame that does // not exist yet. if (tf_info->tf_buf_valid[buf_idx] == 0 || tf_info->tf_buf_display_index_offset[buf_idx] != lookahead_idx) { YV12_BUFFER_CONFIG *out_buf = &tf_info->tf_buf[buf_idx]; av1_temporal_filter(cpi, lookahead_idx, gf_index, &tf_info->frame_diff[buf_idx], out_buf); aom_extend_frame_borders(out_buf, av1_num_planes(cm)); tf_info->tf_buf_gf_index[buf_idx] = gf_index; tf_info->tf_buf_display_index_offset[buf_idx] = lookahead_idx; tf_info->tf_buf_valid[buf_idx] = 1; } } } } YV12_BUFFER_CONFIG *av1_tf_info_get_filtered_buf(TEMPORAL_FILTER_INFO *tf_info, int gf_index, FRAME_DIFF *frame_diff) { if (tf_info->is_temporal_filter_on == 0) return NULL; YV12_BUFFER_CONFIG *out_buf = NULL; for (int i = 0; i < TF_INFO_BUF_COUNT; ++i) { if (tf_info->tf_buf_valid[i] && tf_info->tf_buf_gf_index[i] == gf_index) { out_buf = &tf_info->tf_buf[i]; *frame_diff = tf_info->frame_diff[i]; } } return out_buf; } /*!\endcond */