Google Git
Sign in
aomedia / aom / refs/heads/main / . / av1 / encoder / temporal_filter.c
blob: e8cc145030e0ab3c33abf82fbb398d96b46324aa [file] [log] [blame]
/*
* 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 <float.h>
#include <math.h>
#include <limits.h>
#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 "aom_scale/aom_scale.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);
}
/*!\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 = av1_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;
}
}
int av1_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;
}
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 = av1_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 = av1_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 */