| /* |
| * Copyright (c) 2012 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/content_analysis.h" |
| |
| #include <math.h> |
| #include <stdlib.h> |
| |
| #include "webrtc/system_wrappers/include/cpu_features_wrapper.h" |
| #include "webrtc/system_wrappers/include/tick_util.h" |
| |
| namespace webrtc { |
| |
| VPMContentAnalysis::VPMContentAnalysis(bool runtime_cpu_detection) |
| : orig_frame_(NULL), |
| prev_frame_(NULL), |
| width_(0), |
| height_(0), |
| skip_num_(1), |
| border_(8), |
| motion_magnitude_(0.0f), |
| spatial_pred_err_(0.0f), |
| spatial_pred_err_h_(0.0f), |
| spatial_pred_err_v_(0.0f), |
| first_frame_(true), |
| ca_Init_(false), |
| content_metrics_(NULL) { |
| ComputeSpatialMetrics = &VPMContentAnalysis::ComputeSpatialMetrics_C; |
| TemporalDiffMetric = &VPMContentAnalysis::TemporalDiffMetric_C; |
| |
| if (runtime_cpu_detection) { |
| #if defined(WEBRTC_ARCH_X86_FAMILY) |
| if (WebRtc_GetCPUInfo(kSSE2)) { |
| ComputeSpatialMetrics = &VPMContentAnalysis::ComputeSpatialMetrics_SSE2; |
| TemporalDiffMetric = &VPMContentAnalysis::TemporalDiffMetric_SSE2; |
| } |
| #endif |
| } |
| Release(); |
| } |
| |
| VPMContentAnalysis::~VPMContentAnalysis() { |
| Release(); |
| } |
| |
| VideoContentMetrics* VPMContentAnalysis::ComputeContentMetrics( |
| const VideoFrame& inputFrame) { |
| if (inputFrame.IsZeroSize()) |
| return NULL; |
| |
| // Init if needed (native dimension change). |
| if (width_ != inputFrame.width() || height_ != inputFrame.height()) { |
| if (VPM_OK != Initialize(inputFrame.width(), inputFrame.height())) |
| return NULL; |
| } |
| // Only interested in the Y plane. |
| orig_frame_ = inputFrame.buffer(kYPlane); |
| |
| // Compute spatial metrics: 3 spatial prediction errors. |
| (this->*ComputeSpatialMetrics)(); |
| |
| // Compute motion metrics |
| if (first_frame_ == false) |
| ComputeMotionMetrics(); |
| |
| // Saving current frame as previous one: Y only. |
| memcpy(prev_frame_, orig_frame_, width_ * height_); |
| |
| first_frame_ = false; |
| ca_Init_ = true; |
| |
| return ContentMetrics(); |
| } |
| |
| int32_t VPMContentAnalysis::Release() { |
| if (content_metrics_ != NULL) { |
| delete content_metrics_; |
| content_metrics_ = NULL; |
| } |
| |
| if (prev_frame_ != NULL) { |
| delete[] prev_frame_; |
| prev_frame_ = NULL; |
| } |
| |
| width_ = 0; |
| height_ = 0; |
| first_frame_ = true; |
| |
| return VPM_OK; |
| } |
| |
| int32_t VPMContentAnalysis::Initialize(int width, int height) { |
| width_ = width; |
| height_ = height; |
| first_frame_ = true; |
| |
| // skip parameter: # of skipped rows: for complexity reduction |
| // temporal also currently uses it for column reduction. |
| skip_num_ = 1; |
| |
| // use skipNum = 2 for 4CIF, WHD |
| if ((height_ >= 576) && (width_ >= 704)) { |
| skip_num_ = 2; |
| } |
| // use skipNum = 4 for FULLL_HD images |
| if ((height_ >= 1080) && (width_ >= 1920)) { |
| skip_num_ = 4; |
| } |
| |
| if (content_metrics_ != NULL) { |
| delete content_metrics_; |
| } |
| |
| if (prev_frame_ != NULL) { |
| delete[] prev_frame_; |
| } |
| |
| // Spatial Metrics don't work on a border of 8. Minimum processing |
| // block size is 16 pixels. So make sure the width and height support this. |
| if (width_ <= 32 || height_ <= 32) { |
| ca_Init_ = false; |
| return VPM_PARAMETER_ERROR; |
| } |
| |
| content_metrics_ = new VideoContentMetrics(); |
| if (content_metrics_ == NULL) { |
| return VPM_MEMORY; |
| } |
| |
| prev_frame_ = new uint8_t[width_ * height_]; // Y only. |
| if (prev_frame_ == NULL) |
| return VPM_MEMORY; |
| |
| return VPM_OK; |
| } |
| |
| // Compute motion metrics: magnitude over non-zero motion vectors, |
| // and size of zero cluster |
| int32_t VPMContentAnalysis::ComputeMotionMetrics() { |
| // Motion metrics: only one is derived from normalized |
| // (MAD) temporal difference |
| (this->*TemporalDiffMetric)(); |
| return VPM_OK; |
| } |
| |
| // Normalized temporal difference (MAD): used as a motion level metric |
| // Normalize MAD by spatial contrast: images with more contrast |
| // (pixel variance) likely have larger temporal difference |
| // To reduce complexity, we compute the metric for a reduced set of points. |
| int32_t VPMContentAnalysis::TemporalDiffMetric_C() { |
| // size of original frame |
| int sizei = height_; |
| int sizej = width_; |
| uint32_t tempDiffSum = 0; |
| uint32_t pixelSum = 0; |
| uint64_t pixelSqSum = 0; |
| |
| uint32_t num_pixels = 0; // Counter for # of pixels. |
| const int width_end = ((width_ - 2 * border_) & -16) + border_; |
| |
| for (int i = border_; i < sizei - border_; i += skip_num_) { |
| for (int j = border_; j < width_end; j++) { |
| num_pixels += 1; |
| int ssn = i * sizej + j; |
| |
| uint8_t currPixel = orig_frame_[ssn]; |
| uint8_t prevPixel = prev_frame_[ssn]; |
| |
| tempDiffSum += |
| static_cast<uint32_t>(abs((int16_t)(currPixel - prevPixel))); |
| pixelSum += static_cast<uint32_t>(currPixel); |
| pixelSqSum += static_cast<uint64_t>(currPixel * currPixel); |
| } |
| } |
| |
| // Default. |
| motion_magnitude_ = 0.0f; |
| |
| if (tempDiffSum == 0) |
| return VPM_OK; |
| |
| // Normalize over all pixels. |
| float const tempDiffAvg = |
| static_cast<float>(tempDiffSum) / static_cast<float>(num_pixels); |
| float const pixelSumAvg = |
| static_cast<float>(pixelSum) / static_cast<float>(num_pixels); |
| float const pixelSqSumAvg = |
| static_cast<float>(pixelSqSum) / static_cast<float>(num_pixels); |
| float contrast = pixelSqSumAvg - (pixelSumAvg * pixelSumAvg); |
| |
| if (contrast > 0.0) { |
| contrast = sqrt(contrast); |
| motion_magnitude_ = tempDiffAvg / contrast; |
| } |
| return VPM_OK; |
| } |
| |
| // Compute spatial metrics: |
| // To reduce complexity, we compute the metric for a reduced set of points. |
| // The spatial metrics are rough estimates of the prediction error cost for |
| // each QM spatial mode: 2x2,1x2,2x1 |
| // The metrics are a simple estimate of the up-sampling prediction error, |
| // estimated assuming sub-sampling for decimation (no filtering), |
| // and up-sampling back up with simple bilinear interpolation. |
| int32_t VPMContentAnalysis::ComputeSpatialMetrics_C() { |
| const int sizei = height_; |
| const int sizej = width_; |
| |
| // Pixel mean square average: used to normalize the spatial metrics. |
| uint32_t pixelMSA = 0; |
| |
| uint32_t spatialErrSum = 0; |
| uint32_t spatialErrVSum = 0; |
| uint32_t spatialErrHSum = 0; |
| |
| // make sure work section is a multiple of 16 |
| const int width_end = ((sizej - 2 * border_) & -16) + border_; |
| |
| for (int i = border_; i < sizei - border_; i += skip_num_) { |
| for (int j = border_; j < width_end; j++) { |
| int ssn1 = i * sizej + j; |
| int ssn2 = (i + 1) * sizej + j; // bottom |
| int ssn3 = (i - 1) * sizej + j; // top |
| int ssn4 = i * sizej + j + 1; // right |
| int ssn5 = i * sizej + j - 1; // left |
| |
| uint16_t refPixel1 = orig_frame_[ssn1] << 1; |
| uint16_t refPixel2 = orig_frame_[ssn1] << 2; |
| |
| uint8_t bottPixel = orig_frame_[ssn2]; |
| uint8_t topPixel = orig_frame_[ssn3]; |
| uint8_t rightPixel = orig_frame_[ssn4]; |
| uint8_t leftPixel = orig_frame_[ssn5]; |
| |
| spatialErrSum += static_cast<uint32_t>(abs(static_cast<int16_t>( |
| refPixel2 - static_cast<uint16_t>(bottPixel + topPixel + leftPixel + |
| rightPixel)))); |
| spatialErrVSum += static_cast<uint32_t>(abs(static_cast<int16_t>( |
| refPixel1 - static_cast<uint16_t>(bottPixel + topPixel)))); |
| spatialErrHSum += static_cast<uint32_t>(abs(static_cast<int16_t>( |
| refPixel1 - static_cast<uint16_t>(leftPixel + rightPixel)))); |
| pixelMSA += orig_frame_[ssn1]; |
| } |
| } |
| |
| // Normalize over all pixels. |
| const float spatialErr = static_cast<float>(spatialErrSum >> 2); |
| const float spatialErrH = static_cast<float>(spatialErrHSum >> 1); |
| const float spatialErrV = static_cast<float>(spatialErrVSum >> 1); |
| const float norm = static_cast<float>(pixelMSA); |
| |
| // 2X2: |
| spatial_pred_err_ = spatialErr / norm; |
| // 1X2: |
| spatial_pred_err_h_ = spatialErrH / norm; |
| // 2X1: |
| spatial_pred_err_v_ = spatialErrV / norm; |
| return VPM_OK; |
| } |
| |
| VideoContentMetrics* VPMContentAnalysis::ContentMetrics() { |
| if (ca_Init_ == false) |
| return NULL; |
| |
| content_metrics_->spatial_pred_err = spatial_pred_err_; |
| content_metrics_->spatial_pred_err_h = spatial_pred_err_h_; |
| content_metrics_->spatial_pred_err_v = spatial_pred_err_v_; |
| // Motion metric: normalized temporal difference (MAD). |
| content_metrics_->motion_magnitude = motion_magnitude_; |
| |
| return content_metrics_; |
| } |
| |
| } // namespace webrtc |