External denoiser based on noise estimation and moving object detection.
Improved the existing external denoiser in WebRTC: the filter strength
is adaptive based on the noise level of the whole frame and the moving
object detection result. The adaptive filter effectively removes the
artifacts in previous version, such as trailing and blockiness on moving
objects.
The external denoiser is off by default for now.
BUG=
Review URL: https://codereview.webrtc.org/1822333003
Cr-Commit-Position: refs/heads/master@{#12198}
diff --git a/webrtc/modules/video_processing/util/noise_estimation.cc b/webrtc/modules/video_processing/util/noise_estimation.cc
new file mode 100644
index 0000000..87beac3
--- /dev/null
+++ b/webrtc/modules/video_processing/util/noise_estimation.cc
@@ -0,0 +1,95 @@
+/*
+ * Copyright (c) 2016 The WebRTC project authors. All Rights Reserved.
+ *
+ * Use of this source code is governed by a BSD-style license
+ * that can be found in the LICENSE file in the root of the source
+ * tree. An additional intellectual property rights grant can be found
+ * in the file PATENTS. All contributing project authors may
+ * be found in the AUTHORS file in the root of the source tree.
+ */
+
+#include "webrtc/modules/video_processing/util/noise_estimation.h"
+
+namespace webrtc {
+
+void NoiseEstimation::Init(int width, int height, CpuType cpu_type) {
+ int mb_cols = width >> 4;
+ int mb_rows = height >> 4;
+ consec_low_var_.reset(new uint32_t[mb_cols * mb_rows]());
+ width_ = width;
+ height_ = height;
+ mb_cols_ = width_ >> 4;
+ mb_rows_ = height_ >> 4;
+ cpu_type_ = cpu_type;
+}
+
+void NoiseEstimation::GetNoise(int mb_index, uint32_t var, uint32_t luma) {
+ consec_low_var_[mb_index]++;
+ num_static_block_++;
+ if (consec_low_var_[mb_index] >= kConsecLowVarFrame &&
+ (luma >> 8) < kAverageLumaMax && (luma >> 8) > kAverageLumaMin) {
+ // Normalized var by the average luma value, this gives more weight to
+ // darker blocks.
+ int nor_var = var / (luma >> 12);
+ noise_var_ +=
+ nor_var > kBlockSelectionVarMax ? kBlockSelectionVarMax : nor_var;
+ num_noisy_block_++;
+ }
+}
+
+void NoiseEstimation::ResetConsecLowVar(int mb_index) {
+ consec_low_var_[mb_index] = 0;
+}
+
+void NoiseEstimation::UpdateNoiseLevel() {
+ // TODO(jackychen): Tune a threshold for numb_noisy_block > T to make the
+ // condition more reasonable.
+ // No enough samples implies the motion of the camera or too many moving
+ // objects in the frame.
+ if (num_static_block_ < (0.65 * mb_cols_ * mb_rows_) || !num_noisy_block_) {
+ noise_var_ = 0;
+ noise_var_accum_ = 0;
+ num_static_block_ = 0;
+ num_noisy_block_ = 0;
+#if DISPLAY
+ printf("Not enough samples.\n");
+#endif
+ return;
+ } else {
+ // Normalized by the number of noisy blocks.
+ noise_var_ /= num_noisy_block_;
+ // Get the percentage of static blocks.
+ percent_static_block_ =
+ static_cast<double>(num_static_block_) / (mb_cols_ * mb_rows_);
+#if DISPLAY
+ printf("%d %d fraction = %.3f\n", num_static_block_, mb_cols_ * mb_rows_,
+ percent_static_block_);
+#endif
+ num_noisy_block_ = 0;
+ num_static_block_ = 0;
+ }
+ // For the first frame just update the value with current noise_var_,
+ // otherwise, use the averaging window.
+ if (noise_var_accum_ == 0) {
+ noise_var_accum_ = noise_var_;
+ } else {
+ noise_var_accum_ = (noise_var_accum_ * 15 + noise_var_) / 16;
+ }
+ // Reset noise_var_ for the next frame.
+ noise_var_ = 0;
+#if DISPLAY
+ printf("noise_var_accum_ = %.1f, noise_var_ = %d.\n", noise_var_accum_,
+ noise_var_);
+#endif
+}
+
+uint8_t NoiseEstimation::GetNoiseLevel() {
+ int noise_thr = cpu_type_ ? kNoiseThreshold : kNoiseThresholdNeon;
+ UpdateNoiseLevel();
+ if (noise_var_accum_ > noise_thr) {
+ return 1;
+ }
+ return 0;
+}
+
+} // namespace webrtc