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IEEE International Symposium on Circuits and Systems (IEEE ISCAS)

作者： Li, Daowen Yu, Lu Zhejiang Univ Zhejiang Prov Key Lab Informat Proc Commun & Netw Inst Informat & Commun Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781728103976

Neural network-based filters have shown their potential in removing video compression artifacts. However, previously studied neural networks have achieved boosted filtering performance by continuously increasing network complexity, causing heavy burden on memory cost and computation speed. In this paper, we firstly analyze properties of original residuals which are the difference between original and predicted pixel values. Then an in-loop filter based on low-complexity CNN using residuals(CNNF-R), which are generated after compression and reconstruction from original residuals, is proposed for intra video coding. Insights of designing the network are also demonstrated. Compared with the state-of-the-art video coding standard HEVC, CNNF-R achieves up to 6.8% BD-rate reduction and 4.8% on average under all intra configuration, and 23% on average under random access configuration. Meanwhile, CNNF-R outperforms the previous network VRCNN in terms of nearly 70% decrease in computation complexity, considerable decrease in memory consumption and 1.2% increase in BD-rate reduction.

关键词： Convolutional Neural Network(CNN) Residual Low Complexity In-Loop Filter intra video coding

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Mode-Dependent Templates and Scan Order for H.264/AVC-Based intra Lossless coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2012年第9期21卷 4106-4116页

作者： Gu, Zhouye Lin, Weisi Lee, Bu-Sung Lau, Chiew Tong Sun, Ming-Ting Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Univ Washington Dept Elect Engn Seattle WA 98195 USA

In H.264/advanced video coding (AVC), lossless coding and lossy coding share the same entropy coding module. However, the entropy coders in the H.264/AVC standard were original designed for lossy video coding and do not yield adequate performance for lossless video coding. In this paper, we analyze the problem with the current lossless coding scheme and propose a mode-dependent template (MD-template) based method for intra lossless coding. By exploring the statistical redundancy of the prediction residual in the H.264/AVC intra prediction modes, more zero coefficients are generated. By designing a new scan order for each MD-template, the scanned coefficients sequence fits the H.264/AVC entropy coders better. A fast implementation algorithm is also designed. With little computation increase, experimental results confirm that the proposed fast algorithm achieves about 7.2% bit saving compared with the current H.264/AVC fidelity range extensions high profile.

关键词： Adaptive scanning intra video coding lossless coding mode-dependent templates

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CU Size Decision for Low Complexity HEVC intra coding based on Deep Reinforcement Learning 63

CU Size Decision for Low Complexity HEVC Intra Coding based ...

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63rd IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Jamali, Mohammadreza Coulombe, Stephane Sadreazami, Hamidreza Univ Quebec Ecole Technol Super Dept Software & IT Engn Montreal PQ Canada McGill Univ Bioengn Dept Montreal PQ Canada

ISBN: (纸本)9781728180588

High efficiency video coding (HEVC) uses a quadtree-based structure for coding unit (CU) splitting to effectively encode various video sequences with different visual characteristics. However, this new structure results in a dramatically increased complexity that makes real-time HEVC encoding very challenging. In this paper, we propose a novel CU size decision method based on deep reinforcement learning and active feature acquisition to reduce HEVC intra coding computational complexity and encoding time. The proposed method carries out early splitting and early splitting termination by considering the encoder and CU as an agent-environment system. More specifically, through early splitting, the proposed method precludes the need for rate-distortion optimization at the current level. In addition, through early splitting termination, it disposes of the lower level computations. The proposed method provides a very fast encoder with a small quality penalty. Experimental results show that it achieves a 51.3% encoding time reduction on average with a small quality loss of 0.041 dB for the BD-PSNR, when we compare our method to the HEVC test model.

关键词： coding unit size decision deep reinforcement learning high efficiency video coding (HEVC) H.265 intra video coding low complexity video coding video compression

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Fast HEVC intra Mode Decision Based on RDO Cost Prediction

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IEEE TRANSACTIONS ON BROADCASTING 2019年第1期65卷 109-122页

作者： Jamali, Mohammadreza Coulombe, Stephane Univ Quebec Dept Software Engn & Informat Technol Ecole Technol Super Montreal PQ H3C 1K3 Canada

High efficiency video coding (HEVC) increases the number of intra coding modes to 35 to provide higher coding efficiency than previous video coding standards. This results in an increased encoder complexity, since there are more modes to be processed by the high resource-demanding rate-distortion optimization (RDO). In this paper, we propose a novel method to reduce the HEVC intra mode decision computational complexity and encoding time. This method is based on the prediction of the RDO cost of intra modes from a low-complexity sum of absolute transformed differences-based cost. By predicting the RDO cost, we are able to exclude non-promising modes from further processing and thereby save substantial computations. Also, a gradient-based method, using the Prewitt operator, is proposed to eliminate the non-relevant directional modes from the list of candidates. For even more complexity reduction, a mode classification is proposed to adaptively reduce chroma intra modes based on block texture. Experimental results show that we achieve a 47.3% encoding time reduction on average with a negligible quality loss of 0.062 dB for the Bjontegaard delta peak signal-to-noise ratio when we compare our method to the HEVC test model 15.0.

关键词： High efficiency video coding (HEVC) H.265 video compression intra video coding mode decision

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