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Pseudo-2D-matching based enhancement to high efficiency video coding for screen contents

MULTIMEDIA TOOLS AND APPLICATIONS 2015年第18期74卷 7753-7771页

作者： Wang, Shuhui Lin, Tao Zhou, Kailun Zhang, Peijun Chen, Xianyi Tongji Univ VLSI Lab Shanghai 200092 Peoples R China

Computer screens are rich in discontinuous-tone content besides traditional continuous-tone content. Thus, new video coding tools coherently united into traditional hybrid coding tools are needed to effectively compress screen contents. This paper proposes a Pseudo-2D-matching (P2M) coder based enhancement to High Efficiency Video coding for screen contents. An input Largest coding Unit (LCU) is simultaneously fed into a P2M coder and a traditional hybrid coder. The coder minimizing rate-distortion is selected as the final coder for the LCU. The P2M coder breaks an LCU into many horizontal or vertical line segments and searches matching line segments in the searching-window consisting of previously coded pixels. Since the searching-window is large (a few kilobytes to megabytes) to increase the chance to find a good matching, a hash-table is used to speedup the search. In the P2M coder, three matching modes are used: 1) vertically scanned string matching;2) horizontally scanned 2D-shape-preserved matching;and 3) vertically scanned 2D-shape-preserved matching. All three matching modes are used to code an LCU and the mode minimizing rate-distortion is selected in the P2M coder. The P2M based enhancement achieves significant Bitrate-distortion rate (BD-rate) and subjective visual quality improvement over traditional hybrid coding for screen contents.

关键词： screen content coding Hybrid coding String matching Line segment matching

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Lossless Intra Compression of screen content based on Soft Context Formation

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2016年第4期6卷 508-516页

作者： Strutz, Tilo Leipzig Univ Telecommun HfTL Deutsch Telekom Inst Commun Engn D-04277 Leipzig Germany

The challenge in data compression is to transmit or store a minimum number of bits per sample that should be as close as possible to the number of bits defined by the actual average information content. The latter can be approximated by the contextual entropy. The dilemma is generally that the optimal estimation of contextual symbol probabilities is a kind of artificial-intelligence problem and requires enormous computational efforts. Therefore, practical compression methods typically utilise some pre-knowledge about the data. In image compression, this concerns either autocorrelation properties of natural images, such as photographs, or assumptions about repeating patterns in synthetic data that often can be observed in screen content. This paper presents a novel technique for the estimation of the contextual symbol probabilities with moderate computational complexity. The probability distribution is derived for each single pixel based on a soft context formation and is fed into a full-adaptive arithmetic coder. Applied to synthetic images and images with mixed content up to 8000 colors, the proposed scheme shows bit-savings of about 20% compared to the compression with the HEVC reference software (HM-16.7+SCM-6.0), and it also can compete with methods based on context mixing.

关键词： Color image compression lossless coding probability distribution modelling screen content coding

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A memory access number constraint-based string prediction technique for high throughput SCC implemented in AVS3

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2024年 105卷

作者： Zhao, Liping Yan, Zuge Hu, Keli Feng, Sheng Wang, Jiangda Cao, Xueyan Lin, Tao Shaoxing Univ Dept Comp Sci & Engn Shaoxing Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai Peoples R China Peking Univ Informat Technol R&D Innovat Ctr Beijing Peoples R China Shaoxing Univ Inst Artificial Intelligence Shaoxing Peoples R China Zhejiang Prov Peoples Hosp Canc Ctr Dept Gastroenterol Hangzhou Peoples R China

String prediction (SP) is a highly efficient screen content coding (SCC) tool that has been adopted in international and Chinese video coding standards. SP exhibits a highly flexible and efficient ability to predict repetitive matching patterns. However, SP also suffers from low throughput of decoded display output pixels per memory access, which is synchronized with the decoder clock, due to the high number of memory accesses required to decode an SP coding unit for display. Even in state-of-the-art (SOTA) SP, the worst-case scenario involves two memory accesses for decoding each 4-pixel basic string unit across two memory access units, resulting in a throughput as low as two pixels per memory access (PPMA). To solve this problem, we are the first to propose a technique called memory access number constraint-based string prediction (MANC-SP) to achieve high throughput in SCC. First, a novel MANC-SP framework is proposed, a well-designed memory access number constraint rule is established on the basis of statistical data, and a constrained RDO-based string searching method is presented. Compared with the existing SOTA SP, the experimental results demonstrate that MANC-SP can improve the throughput from 2 to 2.67 PPMA, achieving a throughput improvement of 33.33% while maintaining a negligible impact on coding efficiency and complexity.

关键词： Video coding screen content coding Audio video standard String prediction High throughput

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Very Low Bitrate Semantic Compression of Airplane Cockpit screen content

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IEEE TRANSACTIONS ON MULTIMEDIA 2019年第9期21卷 2157-2170页

作者： Mitrica, Iulia Mercier, Eric Ruellan, Christophe Fiandrotti, Attilio Cagnazzo, Marco Pesquet-Popescu, Beatrice Zodiac Data Syst F-78373 Plaisir France Telecom ParisTech F-75013 Paris France Univ Paris Saclay Telecom ParisTech Informat Proc & Commun Lab F-75013 Paris France

This paper addresses the problem of encoding the video generated by the screen of an airplane cockpit. As other computer screens, cockpit screens consist of computer-generated graphics often atop a natural background. Existing screen content coding schemes fail notably in preserving the readability of textual information at the low bitrates required in avionic applications. We propose a screen coding scheme where textual information is encoded according to the relative semantics rather than in the pixel domain. The encoder localizes textual information, and the semantics of each character are extracted with a convolutional neural network and predictively encoded. Text is then removed via inpainting, and the residual background video is compressed with a standard codec and transmitted to the receiver together with the text semantics. At the decoder side, text is synthesized using the decoded semantics and superimposed over the decoded residual video recovering the original frame. Our proposed scheme offers two key advantages over a semantics-unaware scheme that encodes text in the pixel domain. First, the text readability at the decoder is not compromised by compression artifacts, whereas the relative bitrate is negligible. Second, removal of high-frequency transform coefficients associated with the inpainted text drastically reduces the bitrate of the residual ideo. Experiments with real cockpit video sequences show BD-rate gains up to 82% and 69% over a reference H.265/HEVC encoder and its screen content coding extension. Moreover, our scheme achieves quasi-errorless character recognition already at very low bitrates, whereas even HEVC-SCC needs at least three or four times more bitrate to achieve a comparable error rate.

关键词： HEVC screen content coding cockpit content coding low bitrate character recognition semantic video coding convolutional neural networks compound video compound images

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Hash-Based Line-by-Line Template Matching for Lossless screen Image coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2016年第12期25卷 5601-5609页

作者： Peng, Xiulian Xu, Jizheng Microsoft Res Asia Beijing Peoples R China

Template matching (TM) was proposed in the literature a decade ago to efficiently remove non-local redundancies within an image without transmitting any overhead of displacement vectors. However, the large computational complexity introduced at both the encoder and the decoder, especially for a large search range, limits its widespread use. This paper proposes a hash-based line-by-line template matching (hLTM) for lossless screen image coding, where the non-local redundancy commonly exists in text and graphics parts. By hash-based search, it can largely reduce the search complexity of template matching without an accuracy degradation. Besides, the line-by-line template matching increases prediction accuracy by using a fine granularity. Experimental results show that the hLTM can significantly reduce both the encoding and decoding complexities by 68 and 23 times, respectively, compared with the traditional TM with a search radius of 128. Moreover, when compared with High Efficiency Video coding screen content coding test model SCM-1.0, it can largely improve coding efficiency by up to 12.68% bits saving on screen contents with rich texts/graphics.

关键词： Template matching HEVC screen content coding

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Cloudlet-screen computing: a client-server architecture with top graphics performance

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2013年第2期13卷 96-108页

作者： Lin, Tao Zhou, Kailun Wang, Shuhui Tongji Univ VLSI Lab Shanghai 200092 Peoples R China

This paper presents a three-decoupling-boundary theory and classification for performance analysis of client-server architectures. Based on the analysis, a novel client-server architecture with top graphics performance is proposed. The client is only a display screen plus a few Human-Interface-Devices such as a mouse-keyboard-set or touchscreen with an optional mobile storage. The client is connected to a remote or nearby server (cloudlet) by a low latency link transferring primarily post-GPU display screen and HID data. By following exactly the same most-efficient CPU-GPU-screen graphics rendering pipeline from initial graphics primitives to final pixels as that in the traditional computer graphics architecture developed and optimised in the past decades, the architecture has higher graphics and multimedia performance than any other client-server and cloud-mobile computing architectures, e.g. VNC, Remote Desktop, VDI, Zero-client, and PCoIP. No read back of frame buffers as virtualised screen is necessary, so no CPU/GPU overhead occurs and display latency is minimised.

关键词： pervasive cloud-mobile computing client-server performance analysis screen content coding ubiquitous computing multimedia graphics, video, network

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An Evaluation of screen content Casting over Mobile and Wireless Networks

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WIRELESS PERSONAL COMMUNICATIONS 2017年第3期97卷 4877-4895页

作者： Truong Cong Thang Pham Ngoc Nam Nguyen, Duc V. Tran, Huyen T. Univ Aizu Comp Commun Lab Ikki Machi Aizu Wakamatsu Fukushima 9658580 Japan Hanoi Univ Sci & Technol Hanoi Vietnam

Thanks to the availability of many smart devices, displays, and broadband connections, screen casting/sharing has become an important functionality for user devices. Meanwhile, a new video standard called screen content coding (SCC) is going to be issued to support this trend. This paper presents a standard-compliant implementation and evaluation of SCC streaming to mobile devices. The study is targeted at a feasible design and settings for customer devices, supporting both content-generating side and content-consuming side. The evaluation results help to answer how a sending device should generate screen content videos, and how a receiving device could be implemented and adjusted in time-varying environments of mobile networks and wireless home networks. To the best of our knowledge, this is the first evaluation study for SCC casting.

关键词： screen casting screen content coding E-learning Streaming

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ADAPTING LEARNED IMAGE CODECS TO screen content VIA ADJUSTABLE TRANSFORMATIONS 31

ADAPTING LEARNED IMAGE CODECS TO SCREEN CONTENT VIA ADJUSTAB...

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2024 International Conference on Image Processing

作者： Dogaroglu, H. Burak Koyuncu, A. Burakhan Boev, Atanas Alshina, Elena Steinbach, Eckehard Tech Univ Munich Sch Computat Informat & Technol Munich Germany Huawei Munich Res Ctr Munich Germany Munich Inst Robot & Machine Intelligence Munich Germany

ISBN: (纸本)9798350349405;9798350349399

As learned image codecs (LICs) become more prevalent, their low coding efficiency for out-of-distribution data becomes a bottleneck for some applications. To improve the performance of LICs for screen content (SC) images without breaking backwards compatibility, we propose to introduce parameterized and invertible linear transformations into the coding pipeline without changing the underlying baseline codec's operation flow. We design two neural networks to act as prefilters and postfilters in our setup to increase the coding efficiency and help with the recovery from coding artifacts. Our end-to-end trained solution achieves up to 10% bitrate savings on SC compression compared to the baseline LICs while introducing only 1% extra parameters.

关键词： screen content coding learned image compression prefilter postfilter deep learning

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FAST HEVC TO SCC TRANScoding BASED ON DECISION TREES

FAST HEVC TO SCC TRANSCODING BASED ON DECISION TREES

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IEEE International Conference on Multimedia and Expo (IEEE ICME)

作者： Kuang, Wei Chan, Yui-Lam Tsang, Sik-Ho Siu, Wan-Chi Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Signal Proc Hong Kong Peoples R China

ISBN: (纸本)9781538617373

screen content coding (SCC) is an extension of the High-Efficiency Video coding (HEVC) for encoding screen content videos. However, there are many legacy screen content videos already encoded by HEVC. To efficiently migrate screen content videos from the existing HEVC to the emerging SCC, a machine learning based fast transcoding algorithm is proposed by using decision trees in this paper. To speed up the transcoding process, the intermediate data from both the HEVC decoder side and the SCC encoder side are jointly analyzed. Then the optimal coding unit (CU) sizes are mapped from HEVC to SCC while the mode candidates are adaptively checked according to the decision tree outcomes in the re-encoding process. Experimental results show that an average of 48.20% re-encoding time reduction is achieved with only 1.47% Bjontegaard delta bitrate loss using All Intra (AI) configuration.

关键词： Transcoding High Efficiency Video coding screen content coding machine learning

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Multi-level Latent Fusion in Learning-based Image coding

Multi-level Latent Fusion in Learning-based Image Coding

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Shingala, Jay N. Mohananchettiar, Arunkumar Sharma, Pankaj Yin, Peng Arora, Arjun McCarthy, Sean Lu, Taoran Pu, Fangjun Ittiam Syst Bengaluru Karnataka India Dolby Labs Inc Sunnyvale CA USA

ISBN: (纸本)9781665484855

Learning-based image coding has shown promising results for coding of natural images compared to traditional blockbased coding schemes. However, improvements are needed for screen content coding. Most of the popular learning-based coding approaches are based on variational autoencoders employing Convolutional Neural Networks (CNNs) which are end-to-end trained on a training dataset. The receptive field area of the latents in these architectures increase based on the down-sampling ratio and the kernel size used in each convolution layer. The latents coded from the last layer therefore have a large receptive field size which may not be optimal to code image sources such as screen content or mixed content containing text, logos and small edges. This paper proposes new methods to adaptively fuse and code the latents from different layers. It enables a novel multi-level receptive field based latent coding architecture to achieve better coding performance for a diverse set of contents. Additionally, Multi-Mixture distribution based entropy modeling of latent features and content adaptive latent refinements in the encoder is proposed to bring more coding gains. The experimental results show that the approach can significantly improve the coding efficiency for screen content with average bitrate savings of 36%.

关键词： Deep learning neural network feature pyramid network fusion image compression screen content coding

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