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1 /* | 1 /* |
2 * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved. | 2 * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved. |
3 * | 3 * |
4 * Use of this source code is governed by a BSD-style license | 4 * Use of this source code is governed by a BSD-style license |
5 * that can be found in the LICENSE file in the root of the source | 5 * that can be found in the LICENSE file in the root of the source |
6 * tree. An additional intellectual property rights grant can be found | 6 * tree. An additional intellectual property rights grant can be found |
7 * in the file PATENTS. All contributing project authors may | 7 * in the file PATENTS. All contributing project authors may |
8 * be found in the AUTHORS file in the root of the source tree. | 8 * be found in the AUTHORS file in the root of the source tree. |
9 */ | 9 */ |
10 #include "webrtc/common_video/libyuv/include/scaler.h" | 10 #include "webrtc/common_video/libyuv/include/scaler.h" |
11 #include "webrtc/common_video/libyuv/include/webrtc_libyuv.h" | 11 #include "webrtc/common_video/libyuv/include/webrtc_libyuv.h" |
12 #include "webrtc/modules/video_processing/video_denoiser.h" | 12 #include "webrtc/modules/video_processing/video_denoiser.h" |
13 | 13 |
14 namespace webrtc { | 14 namespace webrtc { |
15 | 15 |
16 VideoDenoiser::VideoDenoiser(bool runtime_cpu_detection) | 16 VideoDenoiser::VideoDenoiser(bool runtime_cpu_detection) |
17 : width_(0), | 17 : width_(0), |
18 height_(0), | 18 height_(0), |
19 filter_(DenoiserFilter::Create(runtime_cpu_detection)) {} | 19 filter_(DenoiserFilter::Create(runtime_cpu_detection)), |
20 ne_(new NoiseEstimation()) {} | |
20 | 21 |
21 void VideoDenoiser::TrailingReduction(int mb_rows, | 22 #if EXPERIMENTAL |
22 int mb_cols, | 23 // Draft. This should be replaced with lib function. |
23 const uint8_t* y_src, | 24 static void CopyStatus(std::unique_ptr<uint8_t[]>* d1, |
24 int stride_y, | 25 const std::unique_ptr<uint8_t[]>& d2, |
25 uint8_t* y_dst) { | 26 int len) { |
26 for (int mb_row = 1; mb_row < mb_rows - 1; ++mb_row) { | 27 for (int i = 0; i < len; ++i) { |
27 for (int mb_col = 1; mb_col < mb_cols - 1; ++mb_col) { | 28 (*d1)[i] = d2[i]; |
28 int mb_index = mb_row * mb_cols + mb_col; | |
29 uint8_t* mb_dst = y_dst + (mb_row << 4) * stride_y + (mb_col << 4); | |
30 const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4); | |
31 // If the number of denoised neighbors is less than a threshold, | |
32 // do NOT denoise for the block. Set different threshold for skin MB. | |
33 // The change of denoising status will not propagate. | |
34 if (metrics_[mb_index].is_skin) { | |
35 // The threshold is high (more strict) for non-skin MB where the | |
36 // trailing usually happen. | |
37 if (metrics_[mb_index].denoise && | |
38 metrics_[mb_index + 1].denoise + metrics_[mb_index - 1].denoise + | |
39 metrics_[mb_index + mb_cols].denoise + | |
40 metrics_[mb_index - mb_cols].denoise <= | |
41 2) { | |
42 metrics_[mb_index].denoise = 0; | |
43 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
44 } | |
45 } else if (metrics_[mb_index].denoise && | |
46 metrics_[mb_index + 1].denoise + | |
47 metrics_[mb_index - 1].denoise + | |
48 metrics_[mb_index + mb_cols + 1].denoise + | |
49 metrics_[mb_index + mb_cols - 1].denoise + | |
50 metrics_[mb_index - mb_cols + 1].denoise + | |
51 metrics_[mb_index - mb_cols - 1].denoise + | |
52 metrics_[mb_index + mb_cols].denoise + | |
53 metrics_[mb_index - mb_cols].denoise <= | |
54 7) { | |
55 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
56 } | |
57 } | |
58 } | 29 } |
59 } | 30 } |
60 | 31 |
32 // Check the mb position(1: close to the center, 3: close to the border). | |
33 static int PositionCheck(int mb_row, int mb_col, int mb_rows, int mb_cols) { | |
34 if ((mb_row >= (mb_rows >> 3)) && (mb_row <= (7 * mb_rows >> 3)) && | |
35 (mb_col >= (mb_cols >> 3)) && (mb_col <= (7 * mb_cols >> 3))) | |
36 return 1; | |
37 else if ((mb_row >= (mb_rows >> 4)) && (mb_row <= (15 * mb_rows >> 4)) && | |
38 (mb_col >= (mb_cols >> 4)) && (mb_col <= (15 * mb_cols >> 4))) | |
39 return 2; | |
40 else | |
41 return 3; | |
42 } | |
43 #endif | |
44 | |
61 void VideoDenoiser::DenoiseFrame(const VideoFrame& frame, | 45 void VideoDenoiser::DenoiseFrame(const VideoFrame& frame, |
62 VideoFrame* denoised_frame) { | 46 VideoFrame* denoised_frame, |
47 VideoFrame* denoised_frame_track) { | |
63 int stride_y = frame.stride(kYPlane); | 48 int stride_y = frame.stride(kYPlane); |
64 int stride_u = frame.stride(kUPlane); | 49 int stride_u = frame.stride(kUPlane); |
65 int stride_v = frame.stride(kVPlane); | 50 int stride_v = frame.stride(kVPlane); |
66 // If previous width and height are different from current frame's, then no | 51 // If previous width and height are different from current frame's, then no |
67 // denoising for the current frame. | 52 // denoising for the current frame. |
68 if (width_ != frame.width() || height_ != frame.height()) { | 53 if (width_ != frame.width() || height_ != frame.height()) { |
69 width_ = frame.width(); | 54 width_ = frame.width(); |
70 height_ = frame.height(); | 55 height_ = frame.height(); |
71 denoised_frame->CreateFrame(frame.buffer(kYPlane), frame.buffer(kUPlane), | 56 denoised_frame->CreateFrame(frame.buffer(kYPlane), frame.buffer(kUPlane), |
72 frame.buffer(kVPlane), width_, height_, | 57 frame.buffer(kVPlane), width_, height_, |
73 stride_y, stride_u, stride_v, kVideoRotation_0); | 58 stride_y, stride_u, stride_v, kVideoRotation_0); |
59 denoised_frame_track->CreateFrame( | |
60 frame.buffer(kYPlane), frame.buffer(kUPlane), frame.buffer(kVPlane), | |
61 width_, height_, stride_y, stride_u, stride_v, kVideoRotation_0); | |
74 // Setting time parameters to the output frame. | 62 // Setting time parameters to the output frame. |
75 denoised_frame->set_timestamp(frame.timestamp()); | 63 denoised_frame->set_timestamp(frame.timestamp()); |
76 denoised_frame->set_render_time_ms(frame.render_time_ms()); | 64 denoised_frame->set_render_time_ms(frame.render_time_ms()); |
65 ne_->SetResolution(width_, height_); | |
77 return; | 66 return; |
78 } | 67 } |
79 // For 16x16 block. | 68 // For 16x16 block. |
80 int mb_cols = width_ >> 4; | 69 int mb_cols = width_ >> 4; |
81 int mb_rows = height_ >> 4; | 70 int mb_rows = height_ >> 4; |
82 if (metrics_.get() == nullptr) | 71 if (metrics_.get() == nullptr) |
83 metrics_.reset(new DenoiseMetrics[mb_cols * mb_rows]()); | 72 metrics_.reset(new DenoiseMetrics[mb_cols * mb_rows]()); |
73 if (d_status_.get() == nullptr) { | |
74 d_status_.reset(new uint8_t[mb_cols * mb_rows]()); | |
75 #if EXPERIMENTAL | |
76 d_status_tmp1_.reset(new uint8_t[mb_cols * mb_rows]()); | |
77 d_status_tmp2_.reset(new uint8_t[mb_cols * mb_rows]()); | |
78 #endif | |
79 x_density_.reset(new uint8_t[mb_cols]()); | |
80 y_density_.reset(new uint8_t[mb_rows]()); | |
81 } | |
82 | |
84 // Denoise on Y plane. | 83 // Denoise on Y plane. |
85 uint8_t* y_dst = denoised_frame->buffer(kYPlane); | 84 uint8_t* y_dst = denoised_frame->buffer(kYPlane); |
86 uint8_t* u_dst = denoised_frame->buffer(kUPlane); | 85 uint8_t* u_dst = denoised_frame->buffer(kUPlane); |
87 uint8_t* v_dst = denoised_frame->buffer(kVPlane); | 86 uint8_t* v_dst = denoised_frame->buffer(kVPlane); |
87 uint8_t* y_dst_track = denoised_frame_track->buffer(kYPlane); | |
88 const uint8_t* y_src = frame.buffer(kYPlane); | 88 const uint8_t* y_src = frame.buffer(kYPlane); |
89 const uint8_t* u_src = frame.buffer(kUPlane); | 89 const uint8_t* u_src = frame.buffer(kUPlane); |
90 const uint8_t* v_src = frame.buffer(kVPlane); | 90 const uint8_t* v_src = frame.buffer(kVPlane); |
91 uint8_t noise_level = ne_->GetNoiseLevel(); | |
91 // Temporary buffer to store denoising result. | 92 // Temporary buffer to store denoising result. |
92 uint8_t y_tmp[16 * 16] = {0}; | 93 uint8_t y_tmp[16 * 16] = {0}; |
93 for (int mb_row = 0; mb_row < mb_rows; ++mb_row) { | 94 for (int mb_row = 0; mb_row < mb_rows; ++mb_row) { |
95 y_density_[mb_row] = 0; | |
96 } | |
97 for (int mb_col = 0; mb_col < mb_cols; ++mb_col) { | |
marpan
2016/03/24 20:56:16
can you use memset here?
jackychen_
2016/03/25 18:45:44
Done.
| |
98 x_density_[mb_col] = 0; | |
99 } | |
100 for (int mb_row = 0; mb_row < mb_rows; ++mb_row) { | |
marpan
2016/03/24 20:56:16
put more comments to explain what this block of co
jackychen_
2016/03/25 18:45:44
Done.
| |
101 for (int mb_col = 0; mb_col < mb_cols; ++mb_col) { | |
102 const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4); | |
103 uint8_t* mb_dst_track = | |
104 y_dst_track + (mb_row << 4) * stride_y + (mb_col << 4); | |
105 int mb_index = mb_row * mb_cols + mb_col; | |
106 #if EXPERIMENTAL | |
107 int pos_factor = PositionCheck(mb_row, mb_col, mb_rows, mb_cols); | |
108 uint32_t thr_var_adp = 16 * 16 * 5 * (noise_level ? pos_factor : 1); | |
109 #else | |
110 uint32_t thr_var_adp = 16 * 16 * 5 * (noise_level + 1); | |
111 #endif | |
112 int brightness = 0; | |
113 for (int i = 0; i < 16; ++i) { | |
114 for (int j = 0; j < 16; ++j) { | |
115 brightness += mb_src[i * stride_y + j]; | |
116 } | |
117 } | |
118 | |
119 // Get the averaged block. | |
marpan
2016/03/30 18:27:19
Get denoised block
| |
120 filter_->MbDenoise(mb_dst_track, stride_y, y_tmp, 16, mb_src, stride_y, 0, | |
121 1, true); | |
122 metrics_[mb_index].var = filter_->Variance16x8( | |
123 mb_dst_track, stride_y, y_tmp, 16, &metrics_[mb_index].sad); | |
124 | |
125 if (metrics_[mb_index].var > thr_var_adp) { | |
126 ne_->ResetConsecLowVar(mb_index); | |
127 d_status_[mb_index] = 1; | |
128 #if EXPERIMENTAL | |
129 if (noise_level == 0 || pos_factor < 3) { | |
130 x_density_[mb_col] += 1; | |
131 y_density_[mb_row] += 1; | |
132 } | |
133 #else | |
134 x_density_[mb_col] += 1; | |
135 y_density_[mb_row] += 1; | |
136 #endif | |
137 } else { | |
138 uint32_t sse_t = 0; | |
139 uint32_t noise_var = filter_->Variance16x8(mb_dst_track, stride_y, | |
140 mb_src, stride_y, &sse_t); | |
141 ne_->GetNoise(mb_index, noise_var, brightness); | |
142 d_status_[mb_index] = 0; | |
143 } | |
144 // Track averaged frame. | |
marpan
2016/03/24 20:56:16
Track denoised frame?
jackychen_
2016/03/25 18:45:45
Done.
| |
145 filter_->CopyMem16x16(y_tmp, 16, mb_dst_track, stride_y); | |
146 } | |
147 } | |
148 | |
149 #if EXPERIMENTAL | |
150 // Draft. This can be optimized. | |
151 int mb_row_min = noise_level ? mb_rows >> 3 : 1; | |
152 int mb_col_min = noise_level ? mb_cols >> 3 : 1; | |
153 int mb_row_max = noise_level ? (7 * mb_rows >> 3) : mb_rows - 2; | |
154 int mb_col_max = noise_level ? (7 * mb_cols >> 3) : mb_cols - 2; | |
155 CopyStatus(&d_status_tmp1_, d_status_, mb_rows * mb_cols); | |
156 // Up left. | |
157 for (int mb_row = mb_row_min; mb_row <= mb_row_max; ++mb_row) { | |
158 for (int mb_col = mb_col_min; mb_col <= mb_col_max; ++mb_col) { | |
159 d_status_tmp1_[mb_row * mb_cols + mb_col] |= | |
160 (d_status_tmp1_[(mb_row - 1) * mb_cols + mb_col] | | |
161 d_status_tmp1_[mb_row * mb_cols + mb_col - 1]); | |
162 } | |
163 } | |
164 CopyStatus(&d_status_tmp2_, d_status_tmp1_, mb_rows * mb_cols); | |
165 CopyStatus(&d_status_tmp1_, d_status_, mb_rows * mb_cols); | |
166 // Bottom left. | |
167 for (int mb_row = mb_row_max; mb_row >= mb_row_min; --mb_row) { | |
168 for (int mb_col = mb_col_min; mb_col <= mb_col_max; ++mb_col) { | |
169 d_status_tmp1_[mb_row * mb_cols + mb_col] |= | |
170 (d_status_tmp1_[(mb_row + 1) * mb_cols + mb_col] | | |
171 d_status_tmp1_[mb_row * mb_cols + mb_col - 1]); | |
172 d_status_tmp2_[mb_row * mb_cols + mb_col] &= | |
173 d_status_tmp1_[mb_row * mb_cols + mb_col]; | |
174 } | |
175 } | |
176 CopyStatus(&d_status_tmp1_, d_status_, mb_rows * mb_cols); | |
177 // Up right. | |
178 for (int mb_row = mb_row_min; mb_row <= mb_row_max; ++mb_row) { | |
179 for (int mb_col = mb_col_max; mb_col >= mb_col_min; --mb_col) { | |
180 d_status_tmp1_[mb_row * mb_cols + mb_col] |= | |
181 (d_status_tmp1_[(mb_row - 1) * mb_cols + mb_col] | | |
182 d_status_tmp1_[mb_row * mb_cols + mb_col + 1]); | |
183 d_status_tmp2_[mb_row * mb_cols + mb_col] &= | |
184 d_status_tmp1_[mb_row * mb_cols + mb_col]; | |
185 } | |
186 } | |
187 CopyStatus(&d_status_tmp1_, d_status_, mb_rows * mb_cols); | |
188 // Bottom right. | |
189 for (int mb_row = mb_row_max; mb_row >= mb_row_min; --mb_row) { | |
190 for (int mb_col = mb_col_max; mb_col >= mb_col_min; --mb_col) { | |
191 d_status_tmp1_[mb_row * mb_cols + mb_col] |= | |
192 (d_status_tmp1_[(mb_row + 1) * mb_cols + mb_col] | | |
193 d_status_tmp1_[mb_row * mb_cols + mb_col + 1]); | |
194 d_status_tmp2_[mb_row * mb_cols + mb_col] &= | |
195 d_status_tmp1_[mb_row * mb_cols + mb_col]; | |
196 } | |
197 } | |
198 #endif | |
199 | |
200 for (int mb_row = 0; mb_row < mb_rows; ++mb_row) { | |
marpan
2016/03/24 20:56:16
put comments to explain this block of code
jackychen_
2016/03/25 18:45:45
Done.
| |
94 for (int mb_col = 0; mb_col < mb_cols; ++mb_col) { | 201 for (int mb_col = 0; mb_col < mb_cols; ++mb_col) { |
95 const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4); | 202 const uint8_t* mb_src = y_src + (mb_row << 4) * stride_y + (mb_col << 4); |
96 uint8_t* mb_dst = y_dst + (mb_row << 4) * stride_y + (mb_col << 4); | 203 uint8_t* mb_dst = y_dst + (mb_row << 4) * stride_y + (mb_col << 4); |
97 int mb_index = mb_row * mb_cols + mb_col; | |
98 // Denoise each MB at the very start and save the result to a temporary | |
99 // buffer. | |
100 if (filter_->MbDenoise(mb_dst, stride_y, y_tmp, 16, mb_src, stride_y, 0, | |
101 1) == FILTER_BLOCK) { | |
102 uint32_t thr_var = 0; | |
103 // Save var and sad to the buffer. | |
104 metrics_[mb_index].var = filter_->Variance16x8( | |
105 mb_dst, stride_y, y_tmp, 16, &metrics_[mb_index].sad); | |
106 // Get skin map. | |
107 metrics_[mb_index].is_skin = MbHasSkinColor( | |
108 y_src, u_src, v_src, stride_y, stride_u, stride_v, mb_row, mb_col); | |
109 // Variance threshold for skin/non-skin MB is different. | |
110 // Skin MB use a small threshold to reduce blockiness. | |
111 thr_var = metrics_[mb_index].is_skin ? 128 : 12 * 128; | |
112 if (metrics_[mb_index].var > thr_var) { | |
113 metrics_[mb_index].denoise = 0; | |
114 // Use the source MB. | |
115 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
116 } else { | |
117 metrics_[mb_index].denoise = 1; | |
118 // Use the denoised MB. | |
119 filter_->CopyMem16x16(y_tmp, 16, mb_dst, stride_y); | |
120 } | |
121 } else { | |
122 metrics_[mb_index].denoise = 0; | |
123 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
124 } | |
125 // Copy source U/V plane. | |
126 const uint8_t* mb_src_u = | 204 const uint8_t* mb_src_u = |
127 u_src + (mb_row << 3) * stride_u + (mb_col << 3); | 205 u_src + (mb_row << 3) * stride_u + (mb_col << 3); |
128 const uint8_t* mb_src_v = | 206 const uint8_t* mb_src_v = |
129 v_src + (mb_row << 3) * stride_v + (mb_col << 3); | 207 v_src + (mb_row << 3) * stride_v + (mb_col << 3); |
130 uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u + (mb_col << 3); | 208 uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u + (mb_col << 3); |
131 uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v + (mb_col << 3); | 209 uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v + (mb_col << 3); |
210 #if EXPERIMENTAL | |
211 if (!d_status_tmp2_[mb_row * mb_cols + mb_col] || | |
212 x_density_[mb_col] * y_density_[mb_row] == 0) { | |
213 #else | |
214 if (x_density_[mb_col] * y_density_[mb_row] == 0) { | |
215 #endif | |
216 if (filter_->MbDenoise(mb_dst, stride_y, y_tmp, 16, mb_src, stride_y, 0, | |
217 noise_level, false) == FILTER_BLOCK) { | |
218 filter_->CopyMem16x16(y_tmp, 16, mb_dst, stride_y); | |
219 } else { | |
220 // Copy y source. | |
221 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
222 } | |
223 } else { | |
224 // Copy y source. | |
225 filter_->CopyMem16x16(mb_src, stride_y, mb_dst, stride_y); | |
226 } | |
132 filter_->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u); | 227 filter_->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u); |
133 filter_->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v); | 228 filter_->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v); |
134 } | 229 } |
135 } | 230 } |
136 // Second round. | 231 |
137 // This is to reduce the trailing artifact and blockiness by referring | 232 #if DISPLAY // Rectangle diagnostics |
138 // neighbors' denoising status. | 233 // Show rectangular region |
139 TrailingReduction(mb_rows, mb_cols, y_src, stride_y, y_dst); | 234 for (int mb_row = 0; mb_row < mb_rows; ++mb_row) { |
235 for (int mb_col = 0; mb_col < mb_cols; ++mb_col) { | |
236 int mb_index = mb_row * mb_cols + mb_col; | |
237 const uint8_t* mb_src_u = | |
238 u_src + (mb_row << 3) * stride_u + (mb_col << 3); | |
239 const uint8_t* mb_src_v = | |
240 v_src + (mb_row << 3) * stride_v + (mb_col << 3); | |
241 uint8_t* mb_dst_u = u_dst + (mb_row << 3) * stride_u + (mb_col << 3); | |
242 uint8_t* mb_dst_v = v_dst + (mb_row << 3) * stride_v + (mb_col << 3); | |
243 uint8_t y_tmp_255[8 * 8]; | |
244 memset(y_tmp_255, 200, 8 * 8); | |
245 // x_density_[mb_col] * y_density_[mb_row] | |
246 if (d_status_[mb_index] == 1) { | |
247 // Paint to red. | |
248 filter_->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u); | |
249 filter_->CopyMem8x8(y_tmp_255, 8, mb_dst_v, stride_v); | |
250 } else if (d_status_tmp2_[mb_row * mb_cols + mb_col] && | |
251 x_density_[mb_col] * y_density_[mb_row]) { | |
252 // Paint to blue. | |
253 filter_->CopyMem8x8(y_tmp_255, 8, mb_dst_u, stride_u); | |
254 filter_->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v); | |
255 } else { | |
256 filter_->CopyMem8x8(mb_src_u, stride_u, mb_dst_u, stride_u); | |
257 filter_->CopyMem8x8(mb_src_v, stride_v, mb_dst_v, stride_v); | |
258 } | |
259 } | |
260 } | |
261 #endif | |
140 | 262 |
141 // Setting time parameters to the output frame. | 263 // Setting time parameters to the output frame. |
142 denoised_frame->set_timestamp(frame.timestamp()); | 264 denoised_frame->set_timestamp(frame.timestamp()); |
143 denoised_frame->set_render_time_ms(frame.render_time_ms()); | 265 denoised_frame->set_render_time_ms(frame.render_time_ms()); |
144 return; | 266 return; |
145 } | 267 } |
146 | 268 |
147 } // namespace webrtc | 269 } // namespace webrtc |
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