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1. 发明申请

US20170070745A1 Perceptual Optimization for Model-Based Video Encoding 审中-公开
标题翻译：基于模型的视频编码的感知优化
公开(公告)号：US20170070745A1
公开(公告)日：2017-03-09
申请号：US15356142
申请日：2016-11-18
申请人： Euclid Discoveries, LLC
发明人： Nigel Lee , Sangseok Park , Myo Tun , Dane P. Kottke , Jeyun Lee , Christopher Weed
IPC分类号： H04N19/513 , H04N19/124 , H04N19/147 , H04N19/61 , H04N19/117 , H04N19/14 , H04N19/159 , H04N19/13
CPC分类号： H04N19/513 , H04N19/117 , H04N19/124 , H04N19/13 , H04N19/139 , H04N19/14 , H04N19/147 , H04N19/159 , H04N19/167 , H04N19/172 , H04N19/176 , H04N19/182 , H04N19/184 , H04N19/527 , H04N19/56 , H04N19/567 , H04N19/61
摘要： Perceptual statistics are used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be generated from encoders that produce motion vectors and employ motion estimation for inter-prediction. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Quality metrics may be used to construct a true motion vector map (TMVM), which refines the TCSF. Spatial complexity maps (SCMs) can be calculated from simple metrics (e.g. block variance, block luminance, SSIM, and edge detection). Importance maps with TCSF, TMVM, and SCM may be used to modify the standard rate-distortion optimization criterion for selecting the optimum encoding solution. Importance maps may modify encoder quantization. The spatial information for the importance maps may be provided by a lookup table based on block variance, where negative and positive spatial QP offsets for block variances are provided.
摘要翻译：感知统计用于计算重要性图，其指示视频帧的哪些区域对于人类视觉系统是重要的。可以从产生运动矢量的编码器产生重要性图，并且对帧间预测采用运动估计。可以从编码器的运动矢量计算时间对比度灵敏度函数（TCSF）。可以使用质量度量来构建真正的运动矢量图（TMVM），其精简TCSF。可以从简单度量（例如块方差，块亮度，SSIM和边缘检测）计算空间复杂度映射（SCM）。使用TCSF，TMVM和SCM的重要性映射可用于修改用于选择最佳编码解决方案的标准速率失真优化标准。重要性地图可能会修改编码器量化。重要性图的空间信息可以由基于块方差的查找表提供，其中提供了用于块方差的负和正空间QP偏移。

2. 发明授权

US11350105B2 Selection of video quality metrics and models to optimize bitrate savings in video encoding applications 有权
公开(公告)号：US11350105B2
公开(公告)日：2022-05-31
申请号：US17144924
申请日：2021-01-08
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , H04N19/124 , H04N19/172 , H04N19/50 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154 , G06T7/00
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at different frame sizes.

3. 发明授权

US10091507B2 Perceptual optimization for model-based video encoding 有权
公开(公告)号：US10091507B2
公开(公告)日：2018-10-02
申请号：US14845067
申请日：2015-09-03
申请人： Euclid Discoveries, LLC
发明人： Nigel Lee , Sangseok Park , Myo Tun , Dane P. Kottke , Jeyun Lee , Christopher Weed
IPC分类号： H04N19/124 , H04N19/139 , H04N19/176 , H04N19/14 , H04N19/527
摘要： Perceptual statistics may be used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be applied to the video encoding process to enhance the quality of encoded bitstreams. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Motion vector quality metrics may be used to construct a true motion vector map (TMVM) that can be used to refine the TCSF. Spatial complexity maps (SCMs) can be calculated from metrics such as block variance, block luminance, SSIM, and edge strength, and the SCMs can be combined with the TCSF to obtain a unified importance map. Importance maps may be used to improve encoding by modifying the criterion for selecting optimum encoding solutions or by modifying the quantization for each target block to be encoded.

4. 发明申请

US20210203951A1 Selection of Video Quality Metrics and Models to Optimize Bitrate Savings in Video Encoding Applications 有权
公开(公告)号：US20210203951A1
公开(公告)日：2021-07-01
申请号：US17144924
申请日：2021-01-08
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , H04N19/124 , H04N19/172 , H04N19/50 , G06T7/00 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at different frame sizes.

5. 发明授权

US11228766B2 Dynamic scaling for consistent video quality in multi-frame size encoding 有权
公开(公告)号：US11228766B2
公开(公告)日：2022-01-18
申请号：US17143929
申请日：2021-01-07
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , H04N19/124 , H04N19/172 , H04N19/50 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154 , G06T7/00
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

6. 发明授权

US09621917B2 Continuous block tracking for temporal prediction in video encoding 有权
公开(公告)号：US09621917B2
公开(公告)日：2017-04-11
申请号：US14532947
申请日：2014-11-04
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , John J. Guo , Jeyun Lee , Sangseok Park , Christopher Weed , Justin Kwan , Nigel Lee
IPC分类号： H04B1/66 , H04N7/12 , H04N11/02 , H04N11/04 , H04N19/56 , H04N19/517 , H04N19/117 , H04N19/105 , H04N19/139 , H04N19/176 , H04N19/513 , H04N19/527 , H04N19/53 , H04N19/58
CPC分类号： H04N19/56 , H04N19/105 , H04N19/117 , H04N19/139 , H04N19/176 , H04N19/513 , H04N19/517 , H04N19/527 , H04N19/53 , H04N19/58
摘要： Continuous block tracking (CBT) tracks macroblock locations over reference frames to produce better inter-predictions than conventional block-based motion estimation/compression. CBT includes frame-to-frame tracking, estimating motion from a frame to a previous frame, and continuous tracking, related frame-to-frame motion vectors to block tracks. Frame-to-frame tracking may include block based or hierarchical motion estimations. CBT combined with enhanced predictive zonal search may create unified motion estimation. Accumulated CBT results may form trajectories for trajectory-based CBT predictions. Metrics measuring continuous track and motion vector quality can assess relative priority of CBT prediction against non-tracker-based predictions and to modify encoding choices. Continuous tracks can be analyzed for goodness-of-fit to translational motion models, with outliers removed from encoding. Translational motion models can be extended to entire frames in adaptive picture type selection. Outputs from CBT used in look-ahead processing, via look-ahead tracking, may provide rate control and scene change detection for the current frame being encoded.

7. 发明申请

US20160073111A1 PERCEPTUAL OPTIMIZATION FOR MODEL-BASED VIDEO ENCODING 审中-公开
标题翻译：基于模型的视频编码的特征优化
公开(公告)号：US20160073111A1
公开(公告)日：2016-03-10
申请号：US14845067
申请日：2015-09-03
申请人： Euclid Discoveries, LLC
发明人： Nigel Lee , Sangseok Park , Myo Tun , Dane P. Kottke , Jeyun Lee , Christopher Weed
IPC分类号： H04N19/124 , H04N19/463 , H04N19/176
CPC分类号： H04N19/124 , H04N19/139 , H04N19/14 , H04N19/176 , H04N19/527
摘要： Perceptual statistics may be used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be applied to the video encoding process to enhance the quality of encoded bitstreams. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Motion vector quality metrics may be used to construct a true motion vector map (TMVM) that can be used to refine the TCSF. Spatial complexity maps (SCMs) can be calculated from metrics such as block variance, block luminance, SSIM, and edge strength, and the SCMs can be combined with the TCSF to obtain a unified importance map. Importance maps may be used to improve encoding by modifying the criterion for selecting optimum encoding solutions or by modifying the quantization for each target block to be encoded.
摘要翻译：可以使用感知统计来计算重要性图，其指示视频帧的哪些区域对于人类视觉系统是重要的。重要性图可以应用于视频编码处理以增强编码比特流的质量。可以从编码器的运动矢量计算时间对比度灵敏度函数（TCSF）。可以使用运动矢量质量度量来构建可用于细化TCSF的真实运动矢量图（TMVM）。可以从诸如块方差，块亮度，SSIM和边缘强度的度量来计算空间复杂度映射（SCM），并且可以将SCM与TCSF组合以获得统一的重要性映射。重要性图可以用于通过修改用于选择最佳编码解决方案的标准或通过修改要编码的每个目标块的量化来改进编码。

8. 发明授权

US11159801B2 Video characterization for smart encoding based on perceptual quality optimization 有权
公开(公告)号：US11159801B2
公开(公告)日：2021-10-26
申请号：US16926089
申请日：2020-07-10
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , H04N19/124 , H04N19/172 , H04N19/50 , G06T7/00 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

9. 发明申请

US20210203950A1 Dynamic Scaling for Consistent Video Quality in Multi-frame Size Encoding 有权
公开(公告)号：US20210203950A1
公开(公告)日：2021-07-01
申请号：US17143929
申请日：2021-01-07
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , H04N19/124 , H04N19/172 , H04N19/50 , G06T7/00 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

10. 发明授权

US10757419B2 Video characterization for smart encoding based on perceptual quality optimization 有权
公开(公告)号：US10757419B2
公开(公告)日：2020-08-25
申请号：US16420796
申请日：2019-05-23
申请人： Euclid Discoveries, LLC
发明人： Dane P. Kottke , Katherine H. Cornog , John J. Guo , Myo Tun , Jeyun Lee , Nigel Lee
IPC分类号： H04N19/146 , G06T7/00 , H04N19/124 , H04N19/50 , H04N19/172 , H04N19/192 , H04N19/179 , H04N19/115 , H04N19/154
摘要： Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

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