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External VNR speed improvement.

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Improved visual quality with 3x times speed-up.
Change list:
 1. Remove second chance filter in temporal denoising filter to mitigate trailing artifact.
 2. Add swap buffer to save one whole-frame memcpy.
 3. Do noise estimation on every N blocks.
 4. Adopt a faster moving object detection algorithm (change the structure).
 5. Refactor the for loops and PositionCheck().
 6. Refactor the function ReduceFalseDetection (RFD).
 7. Fix a bug in TrailingBlock() which causes a mismatch.
 8. Change unit test to support swap buffer test.
 9. Remove CopyMem8x8, use memcpy to copy U/V plane which can be optimized future.
 10. Remove DenoiseMetrics.

Review URL: https://codereview.webrtc.org/1871853003

Cr-Commit-Position: refs/heads/master@{#12340}
This commit is contained in:
jackychen
2016-04-12 23:02:55 -07:00
committed by Commit bot
parent a31fb75e44
commit afaae0d151
14 changed files with 391 additions and 581 deletions
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491
webrtc/modules/video_processing/video_denoiser.cc
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@ -7,10 +7,65 @@
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#include "webrtc/common_video/libyuv/include/scaler.h"
#include "webrtc/common_video/libyuv/include/webrtc_libyuv.h"
#include "webrtc/modules/video_processing/video_denoiser.h"
#if DISPLAY // Rectangle diagnostics
static void CopyMem8x8(const uint8_t* src,
int src_stride,
uint8_t* dst,
int dst_stride) {
for (int i = 0; i < 8; i++) {
memcpy(dst, src, 8);
src += src_stride;
dst += dst_stride;
}
}
static void ShowRect(const std::unique_ptr<DenoiserFilter>& filter,
const std::unique_ptr<uint8_t[]>& d_status,
const std::unique_ptr<uint8_t[]>& moving_edge_red,
const std::unique_ptr<uint8_t[]>& x_density,
const std::unique_ptr<uint8_t[]>& y_density,
const uint8_t* u_src,
const uint8_t* v_src,
uint8_t* u_dst,
uint8_t* v_dst,
int mb_rows_,
int mb_cols_,
int stride_u_,
int stride_v_) {
for (int mb_row = 0; mb_row < mb_rows_; ++mb_row) {
for (int mb_col = 0; mb_col < mb_cols_; ++mb_col) {
int mb_index = mb_row * mb_cols_ + mb_col;
const uint8_t* mb_src_u =
u_src + (mb_row << 3) * stride_u_ + (mb_col << 3);
const uint8_t* mb_src_v =
v_src + (mb_row << 3) * stride_v_ + (mb_col << 3);
uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u_ + (mb_col << 3);
uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v_ + (mb_col << 3);
uint8_t uv_tmp[8 * 8];
memset(uv_tmp, 200, 8 * 8);
if (d_status[mb_index] == 1) {
// Paint to red.
CopyMem8x8(mb_src_u, stride_u_, mb_dst_u, stride_u_);
CopyMem8x8(uv_tmp, 8, mb_dst_v, stride_v_);
} else if (moving_edge_red[mb_row * mb_cols_ + mb_col] &&
x_density[mb_col] * y_density[mb_row]) {
// Paint to blue.
CopyMem8x8(uv_tmp, 8, mb_dst_u, stride_u_);
CopyMem8x8(mb_src_v, stride_v_, mb_dst_v, stride_v_);
} else {
CopyMem8x8(mb_src_u, stride_u_, mb_dst_u, stride_u_);
CopyMem8x8(mb_src_v, stride_v_, mb_dst_v, stride_v_);
}
}
}
}
#endif
namespace webrtc {
VideoDenoiser::VideoDenoiser(bool runtime_cpu_detection)
@ -19,293 +74,255 @@ VideoDenoiser::VideoDenoiser(bool runtime_cpu_detection)
filter_(DenoiserFilter::Create(runtime_cpu_detection, &cpu_type_)),
ne_(new NoiseEstimation()) {}
#if EXPERIMENTAL
// Check the mb position(1: close to the center, 3: close to the border).
static int PositionCheck(int mb_row, int mb_col, int mb_rows, int mb_cols) {
if ((mb_row >= (mb_rows >> 3)) && (mb_row <= (7 * mb_rows >> 3)) &&
(mb_col >= (mb_cols >> 3)) && (mb_col <= (7 * mb_cols >> 3)))
void VideoDenoiser::DenoiserReset(const VideoFrame& frame,
VideoFrame* denoised_frame,
VideoFrame* denoised_frame_prev) {
width_ = frame.width();
height_ = frame.height();
mb_cols_ = width_ >> 4;
mb_rows_ = height_ >> 4;
stride_y_ = frame.stride(kYPlane);
stride_u_ = frame.stride(kUPlane);
stride_v_ = frame.stride(kVPlane);
// Allocate an empty buffer for denoised_frame_prev.
denoised_frame_prev->CreateEmptyFrame(width_, height_, stride_y_, stride_u_,
stride_v_);
// Allocate and initialize denoised_frame with key frame.
denoised_frame->CreateFrame(frame.buffer(kYPlane), frame.buffer(kUPlane),
frame.buffer(kVPlane), width_, height_, stride_y_,
stride_u_, stride_v_, kVideoRotation_0);
// Set time parameters to the output frame.
denoised_frame->set_timestamp(frame.timestamp());
denoised_frame->set_render_time_ms(frame.render_time_ms());
// Init noise estimator and allocate buffers.
ne_->Init(width_, height_, cpu_type_);
moving_edge_.reset(new uint8_t[mb_cols_ * mb_rows_]);
mb_filter_decision_.reset(new DenoiserDecision[mb_cols_ * mb_rows_]);
x_density_.reset(new uint8_t[mb_cols_]);
y_density_.reset(new uint8_t[mb_rows_]);
moving_object_.reset(new uint8_t[mb_cols_ * mb_rows_]);
}
int VideoDenoiser::PositionCheck(int mb_row, int mb_col, int noise_level) {
if (noise_level == 0)
return 1;
else if ((mb_row >= (mb_rows >> 4)) && (mb_row <= (15 * mb_rows >> 4)) &&
(mb_col >= (mb_cols >> 4)) && (mb_col <= (15 * mb_cols >> 4)))
if ((mb_row <= (mb_rows_ >> 4)) || (mb_col <= (mb_cols_ >> 4)) ||
(mb_col >= (15 * mb_cols_ >> 4)))
return 3;
else if ((mb_row <= (mb_rows_ >> 3)) || (mb_col <= (mb_cols_ >> 3)) ||
(mb_col >= (7 * mb_cols_ >> 3)))
return 2;
else
return 3;
return 1;
}
static void ReduceFalseDetection(const std::unique_ptr<uint8_t[]>& d_status,
std::unique_ptr<uint8_t[]>* d_status_tmp1,
std::unique_ptr<uint8_t[]>* d_status_tmp2,
int noise_level,
int mb_rows,
int mb_cols) {
// Draft. This can be optimized. This code block is to reduce false detection
// in moving object detection.
int mb_row_min = noise_level ? mb_rows >> 3 : 1;
int mb_col_min = noise_level ? mb_cols >> 3 : 1;
int mb_row_max = noise_level ? (7 * mb_rows >> 3) : mb_rows - 2;
int mb_col_max = noise_level ? (7 * mb_cols >> 3) : mb_cols - 2;
memcpy((*d_status_tmp1).get(), d_status.get(), mb_rows * mb_cols);
// Up left.
for (int mb_row = mb_row_min; mb_row <= mb_row_max; ++mb_row) {
for (int mb_col = mb_col_min; mb_col <= mb_col_max; ++mb_col) {
(*d_status_tmp1)[mb_row * mb_cols + mb_col] |=
((*d_status_tmp1)[(mb_row - 1) * mb_cols + mb_col] |
(*d_status_tmp1)[mb_row * mb_cols + mb_col - 1]);
void VideoDenoiser::ReduceFalseDetection(
const std::unique_ptr<uint8_t[]>& d_status,
std::unique_ptr<uint8_t[]>* moving_edge_red,
int noise_level) {
// From up left corner.
int mb_col_stop = mb_cols_ - 1;
for (int mb_row = 0; mb_row <= mb_rows_ - 1; ++mb_row) {
for (int mb_col = 0; mb_col <= mb_col_stop; ++mb_col) {
if (d_status[mb_row * mb_cols_ + mb_col]) {
mb_col_stop = mb_col - 1;
break;
}
(*moving_edge_red)[mb_row * mb_cols_ + mb_col] = 0;
}
}
memcpy((*d_status_tmp2).get(), (*d_status_tmp1).get(), mb_rows * mb_cols);
memcpy((*d_status_tmp1).get(), d_status.get(), mb_rows * mb_cols);
// Bottom left.
for (int mb_row = mb_row_max; mb_row >= mb_row_min; --mb_row) {
for (int mb_col = mb_col_min; mb_col <= mb_col_max; ++mb_col) {
(*d_status_tmp1)[mb_row * mb_cols + mb_col] |=
((*d_status_tmp1)[(mb_row + 1) * mb_cols + mb_col] |
(*d_status_tmp1)[mb_row * mb_cols + mb_col - 1]);
(*d_status_tmp2)[mb_row * mb_cols + mb_col] &=
(*d_status_tmp1)[mb_row * mb_cols + mb_col];
// From bottom left corner.
mb_col_stop = mb_cols_ - 1;
for (int mb_row = mb_rows_ - 1; mb_row >= 0; --mb_row) {
for (int mb_col = 0; mb_col <= mb_col_stop; ++mb_col) {
if (d_status[mb_row * mb_cols_ + mb_col]) {
mb_col_stop = mb_col - 1;
break;
}
(*moving_edge_red)[mb_row * mb_cols_ + mb_col] = 0;
}
}
memcpy((*d_status_tmp1).get(), d_status.get(), mb_rows * mb_cols);
// Up right.
for (int mb_row = mb_row_min; mb_row <= mb_row_max; ++mb_row) {
for (int mb_col = mb_col_max; mb_col >= mb_col_min; --mb_col) {
(*d_status_tmp1)[mb_row * mb_cols + mb_col] |=
((*d_status_tmp1)[(mb_row - 1) * mb_cols + mb_col] |
(*d_status_tmp1)[mb_row * mb_cols + mb_col + 1]);
(*d_status_tmp2)[mb_row * mb_cols + mb_col] &=
(*d_status_tmp1)[mb_row * mb_cols + mb_col];
// From up right corner.
mb_col_stop = 0;
for (int mb_row = 0; mb_row <= mb_rows_ - 1; ++mb_row) {
for (int mb_col = mb_cols_ - 1; mb_col >= mb_col_stop; --mb_col) {
if (d_status[mb_row * mb_cols_ + mb_col]) {
mb_col_stop = mb_col + 1;
break;
}
(*moving_edge_red)[mb_row * mb_cols_ + mb_col] = 0;
}
}
memcpy((*d_status_tmp1).get(), d_status.get(), mb_rows * mb_cols);
// Bottom right.
for (int mb_row = mb_row_max; mb_row >= mb_row_min; --mb_row) {
for (int mb_col = mb_col_max; mb_col >= mb_col_min; --mb_col) {
(*d_status_tmp1)[mb_row * mb_cols + mb_col] |=
((*d_status_tmp1)[(mb_row + 1) * mb_cols + mb_col] |
(*d_status_tmp1)[mb_row * mb_cols + mb_col + 1]);
(*d_status_tmp2)[mb_row * mb_cols + mb_col] &=
(*d_status_tmp1)[mb_row * mb_cols + mb_col];
// From bottom right corner.
mb_col_stop = 0;
for (int mb_row = mb_rows_ - 1; mb_row >= 0; --mb_row) {
for (int mb_col = mb_cols_ - 1; mb_col >= mb_col_stop; --mb_col) {
if (d_status[mb_row * mb_cols_ + mb_col]) {
mb_col_stop = mb_col + 1;
break;
}
(*moving_edge_red)[mb_row * mb_cols_ + mb_col] = 0;
}
}
}
static bool TrailingBlock(const std::unique_ptr<uint8_t[]>& d_status,
int mb_row,
int mb_col,
int mb_rows,
int mb_cols) {
int mb_index = mb_row * mb_cols + mb_col;
if (!mb_row || !mb_col || mb_row == mb_rows - 1 || mb_col == mb_cols - 1)
return false;
return d_status[mb_index + 1] || d_status[mb_index - 1] ||
d_status[mb_index + mb_cols] || d_status[mb_index - mb_cols];
bool VideoDenoiser::IsTrailingBlock(const std::unique_ptr<uint8_t[]>& d_status,
int mb_row,
int mb_col) {
bool ret = false;
int mb_index = mb_row * mb_cols_ + mb_col;
if (!mb_row || !mb_col || mb_row == mb_rows_ - 1 || mb_col == mb_cols_ - 1)
ret = false;
else
ret = d_status[mb_index + 1] || d_status[mb_index - 1] ||
d_status[mb_index + mb_cols_] || d_status[mb_index - mb_cols_];
return ret;
}
#endif
#if DISPLAY
void ShowRect(const std::unique_ptr<DenoiserFilter>& filter,
const std::unique_ptr<uint8_t[]>& d_status,
const std::unique_ptr<uint8_t[]>& d_status_tmp2,
const std::unique_ptr<uint8_t[]>& x_density,
const std::unique_ptr<uint8_t[]>& y_density,
const uint8_t* u_src,
const uint8_t* v_src,
uint8_t* u_dst,
uint8_t* v_dst,
int mb_rows,
int mb_cols,
int stride_u,
int stride_v) {
for (int mb_row = 0; mb_row < mb_rows; ++mb_row) {
for (int mb_col = 0; mb_col < mb_cols; ++mb_col) {
int mb_index = mb_row * mb_cols + mb_col;
const uint8_t* mb_src_u =
u_src + (mb_row << 3) * stride_u + (mb_col << 3);
const uint8_t* mb_src_v =
v_src + (mb_row << 3) * stride_v + (mb_col << 3);
uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u + (mb_col << 3);
uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v + (mb_col << 3);
uint8_t y_tmp_255[8 * 8];
memset(y_tmp_255, 200, 8 * 8);
// x_density_[mb_col] * y_density_[mb_row]
if (d_status[mb_index] == 1) {
// Paint to red.
filter->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u);
filter->CopyMem8x8(y_tmp_255, 8, mb_dst_v, stride_v);
#if EXPERIMENTAL
} else if (d_status_tmp2[mb_row * mb_cols + mb_col] &&
x_density[mb_col] * y_density[mb_row]) {
#else
} else if (x_density[mb_col] * y_density[mb_row]) {
#endif
// Paint to blue.
filter->CopyMem8x8(y_tmp_255, 8, mb_dst_u, stride_u);
filter->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v);
} else {
filter->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u);
filter->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v);
void VideoDenoiser::CopySrcOnMOB(const uint8_t* y_src, uint8_t* y_dst) {
// Loop over to copy src block if the block is marked as moving object block
// or if the block may cause trailing artifacts.
for (int mb_row = 0; mb_row < mb_rows_; ++mb_row) {
const int mb_index_base = mb_row * mb_cols_;
const int offset_base = (mb_row << 4) * stride_y_;
const uint8_t* mb_src_base = y_src + offset_base;
uint8_t* mb_dst_base = y_dst + offset_base;
for (int mb_col = 0; mb_col < mb_cols_; ++mb_col) {
const int mb_index = mb_index_base + mb_col;
const uint32_t offset_col = mb_col << 4;
const uint8_t* mb_src = mb_src_base + offset_col;
uint8_t* mb_dst = mb_dst_base + offset_col;
// Check if the block is a moving object block or may cause a trailing
// artifacts.
if (mb_filter_decision_[mb_index] != FILTER_BLOCK ||
IsTrailingBlock(moving_edge_, mb_row, mb_col) ||
(x_density_[mb_col] * y_density_[mb_row] &&
moving_object_[mb_row * mb_cols_ + mb_col])) {
// Copy y source.
filter_->CopyMem16x16(mb_src, stride_y_, mb_dst, stride_y_);
}
}
}
}
#endif
void VideoDenoiser::DenoiseFrame(const VideoFrame& frame,
VideoFrame* denoised_frame,
VideoFrame* denoised_frame_prev,
int noise_level_prev) {
int stride_y = frame.stride(kYPlane);
int stride_u = frame.stride(kUPlane);
int stride_v = frame.stride(kVPlane);
// If previous width and height are different from current frame's, then no
// denoising for the current frame.
bool noise_estimation_enabled) {
// If previous width and height are different from current frame's, need to
// reallocate the buffers and no denoising for the current frame.
if (width_ != frame.width() || height_ != frame.height()) {
width_ = frame.width();
height_ = frame.height();
denoised_frame->CreateFrame(frame.buffer(kYPlane), frame.buffer(kUPlane),
frame.buffer(kVPlane), width_, height_,
stride_y, stride_u, stride_v, kVideoRotation_0);
denoised_frame_prev->CreateFrame(
frame.buffer(kYPlane), frame.buffer(kUPlane), frame.buffer(kVPlane),
width_, height_, stride_y, stride_u, stride_v, kVideoRotation_0);
// Setting time parameters to the output frame.
denoised_frame->set_timestamp(frame.timestamp());
denoised_frame->set_render_time_ms(frame.render_time_ms());
ne_->Init(width_, height_, cpu_type_);
DenoiserReset(frame, denoised_frame, denoised_frame_prev);
return;
}
// For 16x16 block.
int mb_cols = width_ >> 4;
int mb_rows = height_ >> 4;
if (metrics_.get() == nullptr)
metrics_.reset(new DenoiseMetrics[mb_cols * mb_rows]());
if (d_status_.get() == nullptr) {
d_status_.reset(new uint8_t[mb_cols * mb_rows]());
#if EXPERIMENTAL
d_status_tmp1_.reset(new uint8_t[mb_cols * mb_rows]());
d_status_tmp2_.reset(new uint8_t[mb_cols * mb_rows]());
#endif
x_density_.reset(new uint8_t[mb_cols]());
y_density_.reset(new uint8_t[mb_rows]());
}
// Denoise on Y plane.
// Set buffer pointers.
const uint8_t* y_src = frame.buffer(kYPlane);
const uint8_t* u_src = frame.buffer(kUPlane);
const uint8_t* v_src = frame.buffer(kVPlane);
uint8_t* y_dst = denoised_frame->buffer(kYPlane);
uint8_t* u_dst = denoised_frame->buffer(kUPlane);
uint8_t* v_dst = denoised_frame->buffer(kVPlane);
uint8_t* y_dst_prev = denoised_frame_prev->buffer(kYPlane);
const uint8_t* y_src = frame.buffer(kYPlane);
const uint8_t* u_src = frame.buffer(kUPlane);
const uint8_t* v_src = frame.buffer(kVPlane);
uint8_t noise_level = noise_level_prev == -1 ? 0 : ne_->GetNoiseLevel();
// Temporary buffer to store denoising result.
uint8_t y_tmp[16 * 16] = {0};
memset(x_density_.get(), 0, mb_cols);
memset(y_density_.get(), 0, mb_rows);
memset(x_density_.get(), 0, mb_cols_);
memset(y_density_.get(), 0, mb_rows_);
memset(moving_object_.get(), 1, mb_cols_ * mb_rows_);
uint8_t noise_level = noise_estimation_enabled ? ne_->GetNoiseLevel() : 0;
int thr_var_base = 16 * 16 * 5;
// Loop over blocks to accumulate/extract noise level and update x/y_density
// factors for moving object detection.
for (int mb_row = 0; mb_row < mb_rows; ++mb_row) {
for (int mb_col = 0; mb_col < mb_cols; ++mb_col) {
const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4);
uint8_t* mb_dst_prev =
y_dst_prev + (mb_row << 4) * stride_y + (mb_col << 4);
int mb_index = mb_row * mb_cols + mb_col;
#if EXPERIMENTAL
int pos_factor = PositionCheck(mb_row, mb_col, mb_rows, mb_cols);
uint32_t thr_var_adp = 16 * 16 * 5 * (noise_level ? pos_factor : 1);
#else
uint32_t thr_var_adp = 16 * 16 * 5;
#endif
int brightness = 0;
for (int i = 0; i < 16; ++i) {
for (int j = 0; j < 16; ++j) {
brightness += mb_src[i * stride_y + j];
for (int mb_row = 0; mb_row < mb_rows_; ++mb_row) {
const int mb_index_base = mb_row * mb_cols_;
const int offset_base = (mb_row << 4) * stride_y_;
const uint8_t* mb_src_base = y_src + offset_base;
uint8_t* mb_dst_base = y_dst + offset_base;
uint8_t* mb_dst_prev_base = y_dst_prev + offset_base;
for (int mb_col = 0; mb_col < mb_cols_; ++mb_col) {
const int mb_index = mb_index_base + mb_col;
const bool ne_enable = (mb_index % NOISE_SUBSAMPLE_INTERVAL == 0);
const int pos_factor = PositionCheck(mb_row, mb_col, noise_level);
const uint32_t thr_var_adp = thr_var_base * pos_factor;
const uint32_t offset_col = mb_col << 4;
const uint8_t* mb_src = mb_src_base + offset_col;
uint8_t* mb_dst = mb_dst_base + offset_col;
uint8_t* mb_dst_prev = mb_dst_prev_base + offset_col;
// TODO(jackychen): Need SSE2/NEON opt.
int luma = 0;
if (ne_enable) {
for (int i = 4; i < 12; ++i) {
for (int j = 4; j < 12; ++j) {
luma += mb_src[i * stride_y_ + j];
}
}
}
// Get the denoised block.
filter_->MbDenoise(mb_dst_prev, stride_y, y_tmp, 16, mb_src, stride_y, 0,
1, true);
// The variance is based on the denoised blocks in time T and T-1.
metrics_[mb_index].var = filter_->Variance16x8(
mb_dst_prev, stride_y, y_tmp, 16, &metrics_[mb_index].sad);
// Get the filtered block and filter_decision.
mb_filter_decision_[mb_index] =
filter_->MbDenoise(mb_dst_prev, stride_y_, mb_dst, stride_y_, mb_src,
stride_y_, 0, noise_level);
if (metrics_[mb_index].var > thr_var_adp) {
ne_->ResetConsecLowVar(mb_index);
d_status_[mb_index] = 1;
#if EXPERIMENTAL
if (noise_level == 0 || pos_factor < 3) {
x_density_[mb_col] += 1;
y_density_[mb_row] += 1;
// If filter decision is FILTER_BLOCK, no need to check moving edge.
// It is unlikely for a moving edge block to be filtered in current
// setting.
if (mb_filter_decision_[mb_index] == FILTER_BLOCK) {
uint32_t sse_t = 0;
if (ne_enable) {
// The variance used in noise estimation is based on the src block in
// time t (mb_src) and filtered block in time t-1 (mb_dist_prev).
uint32_t noise_var = filter_->Variance16x8(mb_dst_prev, stride_y_,
mb_src, stride_y_, &sse_t);
ne_->GetNoise(mb_index, noise_var, luma);
}
#else
x_density_[mb_col] += 1;
y_density_[mb_row] += 1;
#endif
moving_edge_[mb_index] = 0; // Not a moving edge block.
} else {
uint32_t sse_t = 0;
// The variance is based on the src blocks in time T and denoised block
// in time T-1.
uint32_t noise_var = filter_->Variance16x8(mb_dst_prev, stride_y,
mb_src, stride_y, &sse_t);
ne_->GetNoise(mb_index, noise_var, brightness);
d_status_[mb_index] = 0;
}
// Track denoised frame.
filter_->CopyMem16x16(y_tmp, 16, mb_dst_prev, stride_y);
}
}
#if EXPERIMENTAL
ReduceFalseDetection(d_status_, &d_status_tmp1_, &d_status_tmp2_, noise_level,
mb_rows, mb_cols);
#endif
// Denoise each MB based on the results of moving objects detection.
for (int mb_row = 0; mb_row < mb_rows; ++mb_row) {
for (int mb_col = 0; mb_col < mb_cols; ++mb_col) {
const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4);
uint8_t* mb_dst = y_dst + (mb_row << 4) * stride_y + (mb_col << 4);
const uint8_t* mb_src_u =
u_src + (mb_row << 3) * stride_u + (mb_col << 3);
const uint8_t* mb_src_v =
v_src + (mb_row << 3) * stride_v + (mb_col << 3);
uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u + (mb_col << 3);
uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v + (mb_col << 3);
#if EXPERIMENTAL
if ((!d_status_tmp2_[mb_row * mb_cols + mb_col] ||
x_density_[mb_col] * y_density_[mb_row] == 0) &&
!TrailingBlock(d_status_, mb_row, mb_col, mb_rows, mb_cols)) {
#else
if (x_density_[mb_col] * y_density_[mb_row] == 0) {
#endif
if (filter_->MbDenoise(mb_dst, stride_y, y_tmp, 16, mb_src, stride_y, 0,
noise_level, false) == FILTER_BLOCK) {
filter_->CopyMem16x16(y_tmp, 16, mb_dst, stride_y);
// The variance used in MOD is based on the filtered blocks in time
// T (mb_dst) and T-1 (mb_dst_prev).
uint32_t noise_var = filter_->Variance16x8(mb_dst_prev, stride_y_,
mb_dst, stride_y_, &sse_t);
if (noise_var > thr_var_adp) { // Moving edge checking.
if (ne_enable) {
ne_->ResetConsecLowVar(mb_index);
}
moving_edge_[mb_index] = 1; // Mark as moving edge block.
x_density_[mb_col] += (pos_factor < 3);
y_density_[mb_row] += (pos_factor < 3);
} else {
// Copy y source.
filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y);
moving_edge_[mb_index] = 0;
if (ne_enable) {
// The variance used in noise estimation is based on the src block
// in time t (mb_src) and filtered block in time t-1 (mb_dist_prev).
uint32_t noise_var = filter_->Variance16x8(
mb_dst_prev, stride_y_, mb_src, stride_y_, &sse_t);
ne_->GetNoise(mb_index, noise_var, luma);
}
}
} else {
// Copy y source.
filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y);
}
filter_->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u);
filter_->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v);
}
}
} // End of for loop
} // End of for loop
ReduceFalseDetection(moving_edge_, &moving_object_, noise_level);
CopySrcOnMOB(y_src, y_dst);
// TODO(jackychen): Need SSE2/NEON opt.
// Copy u/v planes.
memcpy(u_dst, u_src, (height_ >> 1) * stride_u_);
memcpy(v_dst, v_src, (height_ >> 1) * stride_v_);
// Set time parameters to the output frame.
denoised_frame->set_timestamp(frame.timestamp());
denoised_frame->set_render_time_ms(frame.render_time_ms());
#if DISPLAY // Rectangle diagnostics
// Show rectangular region
ShowRect(filter_, d_status_, d_status_tmp2_, x_density_, y_density_, u_src,
v_src, u_dst, v_dst, mb_rows, mb_cols, stride_u, stride_v);
ShowRect(filter_, moving_edge_, moving_object_, x_density_, y_density_, u_src,
v_src, u_dst, v_dst, mb_rows_, mb_cols_, stride_u_, stride_v_);
#endif
// Setting time parameters to the output frame.
denoised_frame->set_timestamp(frame.timestamp());
denoised_frame->set_render_time_ms(frame.render_time_ms());
return;
}
} // namespace webrtc