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IEEE 3rd International Conference on Multimedia Information Processing and Retrieval (IEEE MIPR)

作者： Chen, Sijia Chen, Zhenzhong Wang, Yingbin Liu, Shan Wuhan Univ Sch Comp Sci Wuhan Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China Tencent Media Lab Shenzhen Peoples R China Tencent Media Lab Palo Alto CA USA

ISBN: (数字)9781728142722

ISBN: (纸本)9781728142722

In-loop filters are usually used to remove artifacts or further improve coding performance in lossy video compression. Encouraged by the superior performance of deep learning on image restoration, a dense residual convolutional neural network (DRN) based in-loop filter is proposed in this paper for Versatile Video Coding (VVC). The proposed network utilizes residual learning module, dense shortcuts and bottleneck layers, to solve the problems of gradient vanishing, encourage features reuse and save computational resources, respectively. We present the modifications of DRN in terms of network structure, training materials and training process for the trade off between computational complexity and coding efficiency, and valid the effectiveness of the modifications based on the experimental results. Besides, the proposed framework outperforms the VVC reference software with three coding configurations.

关键词： in-loop filtering video compression coding efficiency network complexity

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A DIRECTION-ADAPTIVE IN-loop DEARTIFACTING FILTER FOR VIDEO CODING

A DIRECTION-ADAPTIVE IN-LOOP DEARTIFACTING FILTER FOR VIDEO ...

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15th IEEE International Conference on Image Processing (ICIP 2008)

作者： Dorea, Camilo C. Escoda, Oscar Divorra Yin, Peng Gomila, Cristina Thomson Corp Res Princeton NJ 08540 USA

ISBN: (纸本)9781424417650

Recent video coding strategies, such as H.264/AVC [1], incorporate an in-loop deblocking filter in order to reduce the effects of quantization noise. These techniques are limited to treating blocky artifacts on smooth regions. In order to solve this, sparsity-based filtering techniques have been recently proposed for efficient filtering of edge and textured areas. More recently, direction-adaptive sparsity-based filtering has also allowed to exploit directional features on Intra encoded pictures. This paper proposes a high-performance in-loop filter for deartifacting Intra and Inter encoded video data. This work extends for Inter frames the use of direction-adaptive sparsity-based filtering techniques [2] and it improves performance by adaptively selecting filtering thresholds consistent with quantization noise statistics, local encoding conditions, compression requirements and the original signal. Thresholds are both spatially and temporally adapted to optimize video quality and/or coding cost. Selected thresholds are encoded and transmitted as side information to the decoder. Experimental results show significant bit rate savings and visual quality enhancement when compared to the state-of-theart H.264/AVC codec using in-loop deblocking filtering.

关键词： Video Coding in-loop filtering H.264/AVC Sparse Approximations Redundant Transforrns Quincunx Sampling

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Dense Residual Convolutional Neural Network based In-loop Filter for HEVC 33

Dense Residual Convolutional Neural Network based In-Loop Fi...

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33rd IEEE International Conference on Visual Communications and Image Processing (IEEE VCIP)

作者： Wang, Yingbin Zhu, Han Li, Yiming Chen, Zhenzhong Liu, Shan Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Hubei Peoples R China Wuhan Univ Sch Comp Sci Wuhan Hubei Peoples R China Tencent Media Lab Palo Alto CA USA

ISBN: (纸本)9781538644584

in-loop filtering is a key technique in the state of art video coding standard that plays a significant role in suppressing compression artifacts. Motivated by the latest advances of deep learning, in this paper, we design a dense residual convolutional neural network (DRN) based in-loop filter for High Efficiency Video Coding (HEVC). Taking advantage of both dense shortcuts and residual learning, DRN efficiently exploits the multi-level features to restore the high quality image from the degraded one. Bottleneck layers are employed in DRN in order to adaptively fuse the hierarchical features and saving the computational resources at the same time. Experimental results show that the proposed DRN based in-loop filter can further boost the coding performance, which provides 6.9% BD-rate reduction on average compared to the HEVC baseline. In addition, the proposed DRN outperforms previous CNN based in-loop filters.

关键词： in-loop filtering High Efficiency Video Coding (HEVC) Video Compression Convolutional Neural Network (CNN) Image Restoration

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GPGPU IMPLEMENTATION OF VP9 IN-loop DEBLOCKING FILTER AND IMPROVEMENTS FOR AV1 CODEC 24

GPGPU IMPLEMENTATION OF VP9 IN-LOOP DEBLOCKING FILTER AND IM...

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24th IEEE International Conference on Image Processing (ICIP)

作者： Lei, Zhijun Reddy, Srinath Cherepanov, Victor Deng, Zhipin Intel Corp Santa Clara CA 95051 USA Microsoft Corp Redmond WA 98052 USA

ISBN: (纸本)9781509021758

This paper describes the algorithm and processing flow of the in loop deblocking filter in the VP9 coding standard, one of the most computationally intensive toolsets of the VP9 codec. Due to its inherent data dependency, it is a great challenge to efficiently implement the algorithm on massively parallel computing architectures, such as a General Purpose Graphical Processing Unit (GPGPU). In this paper, we describe the challenges involved in a GPGPU implementation of the VP9 Deblocking filter and introduce an innovative thread dispatching approach to address the parallelization challenges. This approach has been successfully implemented and productized in the VP9 decoder and encoder solutions on Intel GPUs. In order to further improve the parallelism of the deblocking algorithm itself, an improved in-loop deblocking algorithm and process flow is jointly proposed by Intel and Microsoft for the upcoming AV1 codec standard, developed by the Alliance for Open Media (AOM). A description of the algorithm and evaluation of the quality impact of this algorithm is presented with respect to the current state of the art AV1 reference codec.

关键词： deblocking VP9 AV1 in-loop filtering

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A novel parallel deblocking filtering strategy for HEVC/H.265 based on GPU

A novel parallel deblocking filtering strategy for HEVC/H.26...

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4th International Workshop on Embedded Multicore Computing and Applications in conjunction with the 16th IEEE International Conference on High Performance and Communications

作者： Jiang, Wenbin Mei, Hongyan Lu, Feng Jin, Hai Yang, Laurence T. Luo, Bin Chi, Ye Huazhong Univ Sci & Technol Sch Comp Sci & Technol Serv Comp Technol & Syst Lab Cluster & Grid Comp Lab Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Cyber Phys Social Syst CPSS Lab Wuhan 430074 Peoples R China St Francis Xavier Univ Dept Comp Sci Antigonish NS Canada

The deblocking filter in high-efficiency video coding (HEVC) has huge computational complexity because of its high content-adaptive coding structure as well as high-definition. Parallelization for it based on massively parallel architectures such as graphics processing unit becomes an urgent demand. However, a large number of conditional branches and data dependencies severely hinder its efficient parallelization. In this paper, a novel parallel optimization strategy based on graphics processing unit is presented for concurrent deblocking in HEVC/H.265 standard to improve the parallel performance. First, by reducing various conditional branches, a normalization mechanism for instruction stream based on feature vector is proposed, which improves the efficiency of boundary strength computation dramatically. The idea can also be applied to edge discrimination. Second, a parallel mechanism based on an adaptive post-correction is presented to process vertical and horizontal edges filtering concurrently, which improves the processing speed obviously, while producing negligible quality loss. Experimental results show that the strategy presented outperforms the existing state-of-the-art method with accelerating factor up to 32. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： deblocking parallelization HEVC/H.265 GPU in-loop filtering

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SWITCHABLE CNN-BASED SAME-RESOLUTION AND SUPER-RESOLUTION IN-loop RESTORATION FOR NEXT GENERATION VIDEO CODECS 29

SWITCHABLE CNN-BASED SAME-RESOLUTION AND SUPER-RESOLUTION IN...

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IEEE International Conference on Image Processing (ICIP)

作者： Joshi, Urvang Chen, Yue Mukherjee, Debargha Guleryuz, Onur Li, Shan Chong, In Suk Google LLC New York NY 10011 USA

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

We present a common framework for in-loop same-resolution and super-resolution restoration for incorporation into a next-generation video codec. Building on the in-loop filtering pipeline in the AV1 video codec from the Alliance for Open Media (AOM), we first enhance it to support symmetric spatial down-up scaling with better down and upscaling filters, followed by adding switchable frame-level CNNs to restore the reconstructed frames. Furthermore, the architectures for the CNNs used are constrained to be very simple with a relatively small number of parameters and multiply-add operations per decoded pixel to make them practically feasible in hardware. Preliminary results are presented on test sets being used by AOM for their ongoing next-generation video codec (AV2) development effort.

关键词： AV1 super-resolution restoration CNN in-loop filtering

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DECODER-SIDE MOTION ESTIMATION AND WIENER FILTER FOR HEVC

DECODER-SIDE MOTION ESTIMATION AND WIENER FILTER FOR HEVC

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IEEE International Conference on Visual Communications and Image Processing (VCIP)

作者： Chiu, Yi-jen Xu, Lidong Zhang, Wenhao Jiang, Hong Intel Corp 2200 Mission Coll Blvd Santa Clara CA 95054 USA Intel Corp Beijing 100190 Peoples R China

ISBN: (纸本)9781479902880

This paper presents the coding techniques of Decoder-side Motion Vector Derivation (DMVD) and Adaptive loop Filter (ALF) to apply on the state-of-the-art High Efficiency Video Coding (HEVC) standard. Both DMVD and ALF can provide the improvement of coding efficiency on HEVC test Model (HM) reference software, which are reported in multiple proposals during the development period of HEVC. In DMVD algorithm, Motion Vectors (MVs) are derived at video decoder side by utilizing the spatial and temporal correlation among decoded pictures without the signaling of motion vectors from video encoder side. The transmission of MVs from video encoder is skipped and thus better coding efficiency of inter prediction can be achieved. In ALF algorithm, a group of adaptive Wiener filters are applied to the samples of reconstructed pictures to improve the output video visual quality. The filter coefficients can be trained by video encoder and will be conveyed to video decoder signaled by the slice header to apply for the entire pixels in the slice. The utilization of DMVD and ALF can be controlled by the process of coding mode decision at video encoder side based on Rate-Distortion Optimization (RDO) metric. Experiments have demonstrated that the DMVD achieves 0.6%-1.1% BD rate reduction when compared to HM10.0 on the Random Access (RA) test condition. For ALF, average BD rate savings of 1.5%-2.6% are observed compared to HM10.0 under the HM common test condition. Experiment results also demonstrate that the coding gain from the integrated pipe of DMVD and ALF can be additive.

关键词： DMVD motion estimation and motion compensation ALF in-loop filtering HEVC H.265

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Noise suppression filter for video coding 42

Noise suppression filter for video coding

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Conference on Applications of Digital Image Processing XLII

作者： Chernyak, R. Stepin, V. Ikonin, S. Chen, J. Huawei Technol Co Ltd 1 Altufievskoe Shosse Moscow 127506 Russia Futurewei Technol Inc 2330 Cent Expy Santa Clara CA 95050 USA

ISBN: (数字)9781510629684

ISBN: (纸本)9781510629684

In this paper we propose a non-local in-loop filter for video coding called Noise Suppression Filter (NSF). The filter is based on block matching procedure and performs video signal filtering in a transform domain. Filter parameters are derived from a reconstructed signal and do not require additional signaling. NSF can be applied to both luma and chroma components or for luma component only to decrease the complexity. Experimental results shows that the for random access configuration applying NSF for luma and chroma components provides 1.0%, 2.0% and 1.9% of BD-rate saving for Y, Cb and Cr components correspondently with 100% encoding time and 134% decoding time compared to VTM 1.0. For lumaonly NSF demonstrates 1.0% Y BD-rate saving with 100% encoding time and 123% decoding time.

关键词： noise suppression quantization noise removal in-loop filtering block-matching based noise removal

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Programmable 28nm Coprocessor for HEVC/H.265 In-loop Filters

Programmable 28nm Coprocessor for HEVC/H.265 In-Loop Filters

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Hautala, Ilkka Boutellier, Jani Silven, Olli Univ Oulu Dept Comp Sci & Engn Oulu Finland

ISBN: (纸本)9781479953417

High Efficiency Video Coding (HEVC) in-loop filtering includes the deblocking filter (DF) and the sample adaptive offset filter which consume about 20% of the total HEVC decoding time. In this paper a very energy efficient programmable multicore coprocessor for HEVC in-loop filtering is proposed. The coprosessor is placed and routed using leading edge 28nm technology to show that it can be clocked at 1.2 GHz while power consumption is only 207mW including memories. The design is able to filter 101 1080p intra frames per second. The cores can be reprogrammed using a high level language which enables use the high performance coprocessor also for other signal processing algorithms. The proposed coprocessor offers a new alternative between fixed accelerators and general purpose processors for mobile devices in terms of energy efficiency and programmability.

关键词： HEVC in-loop filtering Multicore TTA VLSI

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On Content-Aware Post-Processing: Adapting Statistically Learned Models to Dynamic Content

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2024年第1期20卷 28-28页

作者： Zhang, Yichi Ding, Gongchun Ding, Dandan Ma, Zhan Li, Zhu Hangzhou Normal Univ Hangzhou Peoples R China Nanjing Univ Nanjing Peoples R China Univ Missouri Kansas City Kansas City MO USA

Learning-based post-processing methods generally produce neural models that are statistically optimal on their training datasets. These models, however, neglect intrinsic variations of local video content and may fail to process unseen content. To address this issue, this article proposes a content-aware approach for the post-processing of compressed videos. We develop a backbone network, called BackboneFormer, where a Fast Transformer using Separable Self-Attention, Spatial Attention, and Channel Attention is devised to support underlying feature embedding and aggregation. Furthermore, we introduce Meta-learning to strengthen BackboneFormer for better performance. Specifically, we propose Meta Post-Processing (Meta-PP) which leverages the Meta-learning framework to drive BackboneFormer to capture and analyze input video variations for spontaneous updating. Since the original frame is unavailable to the decoder, we devise a Compression Degradation Estimation model where a low-complexity neural model and classic operators are used collaboratively to estimate the compression distortion. The estimated distortion is then utilized to guide the BackboneFormer model for dynamic updating of weighting parameters. Experimental results demonstrate that the proposed BackboneFormer itself gains about 3.61% Bjontegaard delta bit-rate reduction over Versatile Video Coding in the post-processing task and "BackboneFormer + Meta-PP" attains 4.32%, costing only 50K and 61K parameters, respectively. The computational complexity of MACs is 49k/pixel and 50k/pixel, which represents only about 16% of state-of-the-art methods having similar coding gains.

关键词： VVC in-loop filtering post-processing transformer Meta-learning

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