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A Discrete-Mapping-Based Cross-Component Prediction Paradigm for screen content coding

IEEE TRANSACTIONS ON IMAGE PROCESSING 2024年 33卷 16-26页

作者： Vishwanath, Bharath Zhang, Kai Zhang, Li ByteDance Inc San Diego CA 92121 USA

Cross-component prediction is an important intra-prediction tool in the modern video coders. Existing prediction methods to exploit cross-component correlation include cross-component linear model and its extension of multi-model linear model. These models are designed for camera captured content. For screen content coding, where videos exhibit different signal characteristics, a cross-component prediction model tailored to their characteristics is desirable. As a pioneering work, we propose a discrete-mapping based cross-component prediction model for screen content coding. Our model relies on the core observation that, screen content videos typically comprise of regions with a few distinct colors and luma value (almost always) uniquely conveys chroma value. Based on this, the proposed method learns a discrete-mapping function from available reconstructed luma-chroma pairs and uses this function to derive chroma prediction from the co-located luma samples. To achieve higher accuracy, a multi-filter approach is employed to derive co-located luma values. The proposed method achieves 2.61%, 3.51% and 3.92% Y, U and V bit-rate savings respectively over Enhanced Compression Model (ECM) 4.0, with negligible complexity, for text and graphics media under all-intra configuration.

关键词： Cross-component prediction screen content coding ECM VVC

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Learning-Based Early Transform Skip Mode Decision for VVC screen content coding

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2023年第10期33卷 6041-6056页

作者： Park, Jeeyoon Lee, Jeehwan Kim, Bumyoon Jeon, Byeungwoo Sungkyunkwan Univ Dept Elect & Comp Engn Digital Media Lab Suwon 16410 South Korea

One of the design goals of the recently published international video coding standard, Versatile Video coding (VVC/H.266), is efficient coding of computer-generated video content (commonly referred to as screen content) which exhibits different signal characteristics from the usual camera-captured video (commonly referred as natural content). VVC can perform transform in multiple different ways including skipping the transform itself, which demands much computation for its best selection among many combinatory options. In this paper, we investigate designing a machine-learning-based early transform skip mode decision (ML-TSM) which makes a determination whether or not to skip the transform in an early stage by making a simple classification employing key features designed in such a way to reflect the characteristics of TSM blocks well. Compared with the VVC reference software 14.0, the proposed scheme is verified to reduce computational complexity by 11% and 4% with a Bjontegaard delta bitrate (BDBR) increase of 0.34% and 0.23% respectively under all-intra (AI) and random-access (RA) configurations.

关键词： VVC H266 video coding screen content coding transform skip mode

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Line-based self-referencing string prediction technique for screen content coding in AVS3

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MULTIMEDIA TOOLS AND APPLICATIONS 2023年第15期82卷 23693-23708页

作者： Zhao, Liping Zhou, Qingyang Hu, Keli Feng, Sheng Zhou, Kailun Wang, Weixing Lin, Tao Shaoxing Univ Dept Comp Sci & Engn Shaoxing 312000 Peoples R China Peking Univ Informat Technol R&D Innovat Ctr Shaoxing 312000 Peoples R China Tongji Univ Coll Elect & Informat Engn VLSI Lab Shanghai 200092 Peoples R China

String Prediction (SP) is a very efficient screen content coding (SCC) tool. In SP, the self-referencing string plays an important role to improve coding efficiency. But general self-referencing string has the problem of very low pixel copying throughput and is prohibited in the non-self-referencing based SP which has been adopted in the third-generation Audio Video Standard (AVS3). To overcome the problem and bring back the coding gain of self-referencing string, a line-based self-referencing string (LSRS) enabled SP technique is proposed. Moreover, to keep the pixel copying throughput and coding complexity of LSRS enabled SP the same as non-self-referencing based SP, an unbroken-line decomposition algorithm is presented to decompose an LSRS into multiple non-self-referencing strings. In this way, LSRS can be treated in the same way as a non-self-referencing string with the best trade-off between coding efficiency and complexity. Compared with non-self-referencing based SP, using AVS3 reference software HPM, for twelve SCC common test condition YUV test sequences in text and graphics with motion category and mixed content category, the proposed LSRS technique achieves the average Y BD-rate reduction of 0.81% and 0.59% as well as the maximum Y BD-rate reduction of 2.04% and 1.31% for All Intra and Low Delay configurations, respectively, with almost no additional encoding and decoding complexity. The proposed LSRS enabled SP technique has been adopted in AVS3.

关键词： Audio-video coding standard screen content coding String prediction Self-referencing String decomposition

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ADAPTIVE CHROMA BLOCK VECTOR DERIVATION FROM LUMA FOR screen content coding 49

ADAPTIVE CHROMA BLOCK VECTOR DERIVATION FROM LUMA FOR SCREEN...

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49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Huo, Junyan Hao, Xue Wan, Shuai Yang, Fuzheng Li, Ming Xidian Univ Sch Telecommun Engn Xian Shaanxi Peoples R China Northwestern Polytech Univ Sch Elect & Informat Xian Shaanxi Peoples R China OPPO Mobile Telecommun Corp Ltd Shenzhen Guangdong Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Intra Block Copy (IBC) and Intra Template Matching Prediction (IntraTMP) are two efficient algorithms to sufficiently exploit the correlation in the same picture. Block Vector (BV) is used to represent the displacement between the current block and its reference within the same picture. The BV information of luma can be employed to help the chroma coding efficiently. Based on this feature, an adaptive chroma prediction is proposed to derive the BV of the chroma block from the luma. Two strategies are designed to improve the coding performance, including multiple positions' check and template-based BV refinement. Compared with Enhanced Compression Model (ECM) of beyond VVC, 0.43%, 0.35%, and 0.60% BD-rate savings for Y, Cb, and Cr components are achieved for Class F, and 2.23%, 2.31%, and 2.93% BD-rate savings are provided for Class TGM. We also integrated the proposed method into the VVC Test Model (VTM). A similar coding improvement can be observed. Due to the coding gain and low complexity, the proposed method has been adopted into the beyond VVC exploration and integrated into the latest version of ECM.

关键词： Versatile video coding beyond VVC screen content coding chroma coding block vector

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Overview of screen content coding in Recently Developed Video coding Standards

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年第2期32卷 839-852页

作者： Xu, Xiaozhong Liu, Shan Tencent Amer Palo Alto CA 94306 USA

In recent years, computer-generated texts, graphics, and animations have drawn more attention than ever. These types of media, also known as screen content, have become increasingly popular due to their widespread applications. To address the need for efficient coding of such content, several coding tools have been developed and have made great advances in terms of coding efficiency. The inclusion of screen content coding features in some recently developed video coding standards (namely, HEVC SCC, VVC, AVS3, AV1 and EVC) demonstrates the importance of supporting such features. This paper provides an overview and comparative study of screen content coding technologies, as well as discussions on the performance and complexity of the tools developed in these standards.

关键词： Encoding Standards Tools Decoding Hardware Bandwidth Writing screen content coding intra block copy transform skip residue coding BDPCM palette mode intra string copy deblocking

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A string matching based ultra-low complexity lossless screen content coding technique

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第2期81卷 2043-2063页

作者： Yang, Yufen Lin, Tao Zhao, Liping Zhou, Kailun Wang, Shuhui Tongji Univ Coll Elect & Informat Engn VLSI Lab Shanghai 200092 Peoples R China Shaoxing Univ Dept Comp Sci & Engn Shaoxing 312000 Peoples R China Peking Univ Informat Technol R&D Innovat Ctr Shaoxing 312000 Peoples R China

screen contents have become a popular image type driven by the growing market for transferring display screen between devices, especially mobile devices. Due to the ultra-high quality display featured in most of nowadays mobile devices, lossless screen content coding (SCC) is usually required or preferred. Mobile devices also require ultra-low power consumption in all tasks including SCC. To address these issues, this paper proposes an ultra-low coding complexity technique based on string matching for high efficiency lossless SCC. The technique covers three major coding phases of fast searching, prediction, and entropy coding. Condensed hash table (CHT) based fast searching is proposed to speed-up reference string searching process. Coplanar prediction (CP) and predictor-dependent residual (PDR) are presented to first efficiently predict an unmatchable pixel using multiple neighboring pixels and then further reduce the entropy of prediction residuals. To achieve a good trade-off between coding complexity and efficiency, 4-bit-aligned variable length code (4bVLC) and byte-aligned multi-variable-length-code (BMVLC) are proposed to code the prediction residuals and three string matching parameters, respectively. For 184 screen content images commonly used, compared with X265 and PNG in the default configuration and lossless mode, the proposed technique achieves 35.67% less total compressed bytes with only 0.96% encoding and 1.54% decoding runtime, and 10.04% less total compressed bytes with only 6.83% encoding and 24.32% decoding runtime, respectively. The proposed technique also outperforms X265 and PNG in all other configurations. For twelve HEVC-SCC CTC images, compared with PNG in fast, default and slow configurations and X265 in ultrafast and default configurations, the proposed technique shows significant advantage with both high coding efficiency and ultra-low coding complexity.

关键词： screen content coding String matching Prediction coding Variable length code Hash table

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Efficient coding unit classifier for HEVC screen content coding based on machine learning

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2022年第2期19卷 375-390页

作者： Elsawy, Nabila Sayed, Mohammed S. Farag, Fathi Zagazig Univ Dept Elect & Commun Engn Zagazig Egypt Egypt Japan Univ Sci & Technol Dept Elect & Commun Engn Borg El Arab Egypt

The Video coding Joint Collaboration team (JCT-VC) has been working on an emerging standard for screen content coding (SCC) as an extension of high efficiency video coding (HEVC) standard known as HEVC-SCC. The two powerful coding mechanisms used in HEVC-SCC are intra block copy (IBC) and palette coding (PLT). These techniques achieve the best coding efficiency at the expense of extremely high computational complexity. Therefore, we propose a new technique to minimize computational complexity by skipping undesired modes and retaining coding efficiency. A fast intra mode decision approach is suggested based on efficient CU classification. Our proposed solution depends on categorizing a CU as a natural content block (NCB) or a screen content block (SCB). Two classifiers are used for the classification process. The first one is a neural network (NN) classifier, and the other is an AdaBoost classifier, which depends on a boosted decision stump algorithm. The two classifiers predict the CU type individually and the final decision for CU classification depends on both of them. The experimental results reveal that the suggested technique significantly decreases encoding time without sacrificing coding efficiency. The suggested framework can achieve a 26.13% encoding time reduction on average with just a 0.81% increase in Bjontegaard Delta bit-rate (BD-Rate). Furthermore, the suggested framework saves encoding time by 51.5% on average for a set of NC sequences recommended for standard HEVC tests with minimal performance degradation. The proposed strategy has been merged with an existing methodology to accelerate the process even further.

关键词： HEVC screen content coding Neural network AdaBoost classifier

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Enhanced Intra String Copy for screen content coding in AVS3

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IEEE ACCESS 2022年 10卷 80403-80414页

作者： Zhao, Liping Wang, Huihui Zhou, Qingyang Zhang, Wenjuan Zhou, Kailun Hu, Keli Lin, Tao Shaoxing Univ Dept Comp Sci & Engn Shaoxing 312000 Peoples R China Peking Univ Informat Technol Res & Dev Innovat Ctr Shaoxing 312000 Peoples R China Tongji Univ Coll Elect & Informat Engn VLSI Lab Shanghai 200092 Peoples R China

Driven by growing applications that use computer screens as interfaces for daily remote interactions, almost all current video coding standards have included screen content coding (SCC) tools. Recently, an efficient SCC tool called intra string copy (ISC) has been adopted in the third-generation of audio video coding standard in China (AVS3). ISC has two coding unit (CU) level sub-modes: fully-matching-string and partially-matching-string based string prediction (FPSP) sub-mode and equal-value-string, unit-basis-vector-string, and unmatched-pixel-string based string prediction (EUSP) sub-mode. To further improve the coding efficiency of SCC, this paper proposes four enhancement techniques of ISC (EISC), including CU partition improvements, point vector (PV) relocation and reactivation, line-based overlapping string prediction, and an optimized coding method for string length in the EUSP sub-mode. Compared with the latest AVS3 reference software HPM with EISC disabled, using AVS3 SCC common test condition and YUV test sequences in text and graphics with motion and mixed content categories, the proposed technique achieves an average Y BD-rate reduction of 2.39% and 1.49% for all intra (AI) and low-delay B (LDB) configurations, respectively, with low additional encoding complexity and almost no additional decoding complexity. All proposed ISC enhancement techniques have been adopted in AVS3.

关键词： Encoding Complexity theory Copper Standards Frequency modulation Hardware Transforms Video coding standard screen content coding intra string copy string split point vector

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A CROSS-COMPONENT PREDICTION MODEL FOR screen content coding

A CROSS-COMPONENT PREDICTION MODEL FOR SCREEN CONTENT CODING

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Picture coding Symposium (PCS)

作者： Vishwanath, Bharath Zhang, Kai Zhang, Li Bytedance Inc San Diego CA 92101 USA

ISBN: (纸本)9781665492577

Current video coding schemes such as VVC and ECM employ separate palette coding for luma and chroma components under dual-tree structure, ignoring cross-component correlations. Although there are linear and multi-modal linear models to capture cross-component correlations, such models are not tailored for screen content sequences. To address this, we propose a novel cross-component prediction model for screen content sequences. The proposed method builds on the core observation that, regions of screen content sequences comprise of few distinct colors and luma value (almost always) uniquely conveys chroma values. In the light of this observation, the proposed method derives chroma prediction based on a discrete mapping function between luma and chroma values. Specifically, the method simply remembers the reconstructed luma values and their corresponding chroma values in a look-up table and employs this look-up table for cross-component prediction for the current chroma block. To achieve higher accuracy, a multi-filter approach is employed to derive co-located luma values. For an example configuration, the proposed method achieves 1.37%, 1.08% and 1.68% Y, U and V bit-rate savings respectively over ECM 3.1, for text and graphics media under all-intra configuration, demonstrating its efficacy.

关键词： palette coding cross-component prediction screen content coding ECM VVC

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An Open Video Dataset For screen content coding

An Open Video Dataset For Screen Content Coding

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Picture coding Symposium (PCS)

作者： Wang, Yingbin Zhao, Xin Xu, Xiaozhong Liu, Shan Lei, Zhijun Afonso, Mariana Norkin, Andrey Daede, Thomas Tencent Shenzhen Peoples R China Meta Platforms Inc Menlo Pk CA USA Netflix Inc Los Gatos CA USA Vimeo Inc New York NY USA

ISBN: (纸本)9781665492577

In recent years, screen content video is becoming increasingly popular in several major video applications, such as video recording and video conferencing. Due to the unique features of screen content videos that are not captured by camera sensors but produced artificially, dedicated coding tools have been developed for achieving significant compression efficiency gain. In recognition of the popularity of screen content applications, an open video dataset for screen content is proposed in this paper for the development of screen content coding technologies. The proposed video dataset consists of 12 typical screen content type video clips that are publicly available. In addition, to better understand the characteristics of the proposed video dataset, several major screen content coding tools in AOMedia Video 1 (AV1) have been evaluated on this dataset and analyzed in this paper.

关键词： screen content coding video dataset AOMedia AV1 AVM

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