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2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Ravelli, Emmanuel Melkote, Vinay Nanjundaswamy, Tejaswi Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9781424442966

MPEG-4 High-Definition Advanced Audio coding (HD-AAC) enables scalable-to-lossless (SLS) audio coding with an Advanced Audio coding (AAC) base layer, and fine-grained enhancements based on the MPEG SLS standard. While the AAC core offers better perceptual quality at lossy bit-rates, its inclusion has been observed to compromise the ultimate lossless compression performance as compared to the SLS 'non-core' (i.e., without an AAC base layer) codec. In contrast, the latter provides excellent lossless compression but with significantly degraded audio quality at low bit-rates. We propose a trellis-based approach to directly optimize the trade-off between the quality of the AAC core and the lossless compression performance of SLS. Simulations to test the effectiveness of the approach demonstrate the capability to adjust the trade-off to match application specific needs. Moreover, such optimization can in fact achieve an AAC core of superior perceptual quality while maintaining state-of-the-art (and surprisingly sometimes even better) lossless compression, all this in compliance with the HD-AAC standard.

关键词： Audio coding lossless coding AAC SLS ratedistortion optimization

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Adaptive Neural-Network-Based lossless Image Coder with Preprocessed Input Data

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APPLIED SCIENCES-BASEL 2025年第5期15卷 2603-2603页

作者： Ulacha, Grzegorz Stasinski, Ryszard West Pomeranian Univ Technol Fac Comp Sci & Informat Technol PL-71210 Szczecin Poland Poznan Univ Tech Inst Multimedia Telecommun PL-60965 Poznan Poland

It is shown in this paper that the appropriate preprocessing of input data may result in an important reduction of Artificial Neural Network (ANN) training time and simplification of its structure, while improving its performance. The ANN is working as a data predictor in a lossless image coder. Its adaptation is done for each coded pixel separately;no initial training using learning image sets is necessary. This means that there is no extra off-line time needed for initial ANN training, and there are no problems with network overfitting. There are two concepts covered in this paper: Replacement of image pixels by their differences diminishes data variability and increases ANN convergence (Concept 1);Preceding ANN by advanced predictors reduces ANN complexity (Concept 2). The obtained codecs are much faster than one without modifications, while their data compaction properties are clearly better. It outperforms the JPEG-LS codec by approximately 10%.

关键词： Artificial Neural Network image coding lossless coding

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SAMPLE-BASED WEIGHTED PREDICTION FOR lossless ENHANCEMENT LAYER coding IN SHVC

SAMPLE-BASED WEIGHTED PREDICTION FOR LOSSLESS ENHANCEMENT LA...

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IEEE International Conference on Image Processing

作者： Andreas Heindel Eugen Wige Andre Kaup Multimedia Communications and Signal Processing University of Erlangen-Nuremberg

ISBN: (纸本)9781479957521

Many professional applications require video content to be compressed in a lossless manner. However, often it is also advantageous to have access to a lossy coded version of the same video content, for example for preview purposes. In this paper the Sample-based Weighted Prediction (SWP) algorithm is applied for two-layer lossy to lossless scalable video compression with SHVC. This means that lossy compression is used for the first layer, the so-called base layer, and lossless compression is used for the second layer, also referred to as enhancement layer. In order to increase the coding efficiency of the enhancement layer the SWP algorithm is used for sample-wise prediction. Depending on the quantization parameter for the base layer, significant bitrate savings considering both layers of up to 8.38% (up to 6.20% on average) compared to the unmodified SHVC reference software can be achieved.

关键词： lossless coding Sample-based prediction Scalable coding SHVC

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IMPROVED HEVC lossless COMPRESSION USING TWO-STAGE coding WITH SUB-FRAME LEVEL OPTIMAL QUANTIZATION VALUES

IMPROVED HEVC LOSSLESS COMPRESSION USING TWO-STAGE CODING WI...

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IEEE International Conference on Image Processing

作者： Xun Cai Qunshan Gu Dept. of EECS Massachusetts Inst. of Technol. Cambridge MA USA

ISBN: (纸本)9781479957521

lossless video coding is used when perfect preservation of video data is required. In HEVC, lossless coding is accomplished by bypassing the transform and quantization stages. Prediction residuals are coded with the entropy coder in the spatial domain. In this paper, two-stage coding with sub-frame adaptive quantization is proposed. The DCT is firstly applied to the prediction residuals and the DCT coefficients are quantized. The quantized DCT coefficients and the quantization error are coded. Adaptive quantization parameters are used for each coding Unit. Simulation results show that the proposed method significantly outperforms the HEVC lossless coding.

关键词： data compression discrete cosine transforms entropy codes quantisation (signal) video coding coding unit discrete cosine transform entropy coder improved HEVC lossless compression lossless video coding perfect video data preservation prediction residuals quantization error quantized DCT coefficients spatial domain sub-frame adaptive quantization parameter sub-frame level optimal quantization values two-stage coding Discrete cosine transforms Encoding Entropy Image coding Quantization (signal) Video coding HEVC lossless coding adaptive quantization discrete cosine transforms Video coding Quantization lossless compression spatial domain Entropy coding adaptive quantization lossless coding image coding Data compression entropy High efficiency video coding

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JOINT OPTIMIZATION OF THE PERCEPTUAL CORE AND lossless COMPRESSION LAYERS IN SCALABLE AUDIO coding

JOINT OPTIMIZATION OF THE PERCEPTUAL CORE AND LOSSLESS COMPR...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Emmanuel Ravelli Vinay Melkote Tejaswi Nanjundaswamy Kenneth Rose Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106-9560 USA

ISBN: (纸本)9781424442959;9781424442966

关键词： Audio coding lossless coding AAC SLS rate-distortion optimization Audio coding lossless compression automatic amplitude control Selective laser sintering Rate distortion lossless coding Audio core

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lossless SCREEN CONTENT coding IN HEVC BASED ON SAMPLE-WISE MEDIAN AND EDGE PREDICTION

LOSSLESS SCREEN CONTENT CODING IN HEVC BASED ON SAMPLE-WISE ...

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IEEE International Conference on Image Processing

作者： Victor Sanchez Dept. of Computer Science University of Warwick

ISBN: (纸本)9781479983407

The generation of screen content (SC) videos has considerably increased with the popularity of multimedia applications such as video conferencing, remote desktop sharing and remote education. SC videos, as opposed to natural video sequences, are challenging to compress due to the high number of sharp edges. This paper proposes the sample-based angular prediction with median and edge prediction (SAP-ME), a novel intra-prediction method for lossless coding of SC videos. SAP-ME incorporates the advantages of three types of sample-wise intra-prediction;namely, DPCM-based angular intra-prediction, median prediction and edge prediction. By using rate distortion optimization, SAP-ME selects among these three types of predictions to accurately predict directional patterns, smooth regions and sharp edges, with a low computational complexity. Evaluation results on a variety of SC videos show that SAP-ME attains average bit-rate reductions of 16.13% over current HEVC intra-prediction coding for lossless coding.

关键词： HEVC lossless intra-prediction coding Screen content DPCM Edge predictor Median predictor differential pulse code modulation STANDARD SAMPLE Video sequences Videotapes High efficiency video coding Screen Scandium Videoconferencing lossless coding lossless compression edges Screens SCREEN FILTERS MULTIMEDIA APPLICATION telecommunication standards

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Developing Requirements for a Visually lossless Display Stream coding System Open Standard

Developing Requirements for a Visually Lossless Display Stre...

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SMPTE Technical Conference

作者： Dale Stolitzka Samsung Display Company 217 Devcon Drive San Jose CA 95122

ISBN: (纸本)9781629938370

VESA (The Video Electronics Standards Association) is developing a standard for a visually lossless coding system to be used for the compression of high-bandwidth display data streams. This coding system will complement digital display interface technologies to increase pixel rates or save system power, or both. The display stream coding system is primarily being designed to meet the increased pixel rate needed in high resolution displays expected in the next few years. — This paper recounts VESA's process that led to compression requirements, the selection of a coding system baseline, and strategies to evaluate a visually lossless coding system for consumer electronics and commercial displays. Key concepts in this paper evolved from discussions and documents of VESA's Display Stream Compression Task Group that have been made available to the author with permission from VESA. The Display Stream Compression Standard is forthcoming for publication in the first quarter of 2014.

关键词： Data compression Display stream compression Open standard Image coding system Requirements Data compression Open Standard streams consumer electronics coding coding systems permission lossless coding lossless compression Display resolution

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Highly Parallel Line-Based Image coding for Many Cores

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2012年第1期21卷 196-206页

作者： Peng, Xiulian Xu, Jizheng Zhou, You Wu, Feng Microsoft Res Asia Beijing 100190 Peoples R China

Computers are developing along with a new trend from the dual-core and quad-core processors to ones with tens or even hundreds of cores. Multimedia, as one of the most important applications in computers, has an urgent need to design parallel coding algorithms for compression. Taking intraframe/image coding as a start point, this paper proposes a pure line-by-line coding scheme (LBLC) to meet the need. In LBLC, an input image is processed line by line sequentially, and each line is divided into small fixed-length segments. The compression of all segments from prediction to entropy coding is completely independent and concurrent at many cores. Results on a general-purpose computer show that our scheme can get a 13.9 times speedup with 15 cores at the encoder and a 10.3 times speedup at the decoder. Ideally, such near-linear speeding relation with the number of cores can be kept for more than 100 cores. In addition to the high parallelism, the proposed scheme can perform comparatively or even better than the H. 264 high profile above middle bit rates. At near-lossless coding, it outperforms H. 264 more than 10 dB. At lossless coding, up to 14% bit-rate reduction is observed compared with H. 264 lossless coding at the high 4: 4: 4 profile.

关键词： Image coding lossless coding many cores

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Binary medical image compression using the volumetric run-length approach

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IMAGING SCIENCE JOURNAL 2019年第3期67卷 123-135页

作者： Aldemir, Erdogan Tohumoglu, Gulay Selver, M. Alper Dokuz Eylul Univ Grad Sch Nat & Appl Sci Izmir Turkey Dokuz Eylul Univ Dept Elect & Elect Engn Izmir Turkey

Image compression has become an inevitable tool along with the advancing medical data acquisition and telemedicine systems. The run-length encoding (RLE), one of the most effective and practical lossless compression techniques, is widely used in two-dimensional space with common scanning forms such as zigzag and linear. In this study, an algorithm which takes advantage of the potential simplicity of the run-length algorithm is devised in a volumetric approach for three-dimensional (3D) binary medical data. The proposed algorithm, namely 3D-RLE, being different from the two-dimensional approach that utilizes only intra-slice correlations, is designed to compress binary volumetric data by employing also the inter-slice correlation between the voxels. Furthermore, it is extended to several scanning forms such as Hilbert and perimeter to determine an optimal scanning procedure coherent with the morphology of the segmented organ in data. The algorithm is employed on four datasets for a comprehensive assessment. Numerical simulation results demonstrated that the performance of the algorithm is 1:30 better than those of the state-of-the-art techniques, on average. [GRAPHICS] .

关键词： 3D medical image compression lossless coding run-length encoding

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Highly Efficient Multiview Depth coding Based on Histogram Projection and Allowable Depth Distortion

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2021年 30卷 402-417页

作者： Zhang, Yun Zhu, Linwei Hamzaoui, Raouf Kwong, Sam Ho, Yo-Sung Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China De Montfort Univ Sch Engn & Sustainable Dev Fac Comp Engn & Media Leicester LE1 9BH Leics England City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Gwangju Inst Sci & Technol Sch Elect Engn & Comp Sci Gwangju 500712 South Korea

Mismatches between the precisions of representing the disparity, depth value and rendering position in 3D video systems cause redundancies in depth map representations. In this paper, we propose a highly efficient multiview depth coding scheme based on Depth Histogram Projection (DHP) and Allowable Depth Distortion (ADD) in view synthesis. Firstly, DHP exploits the sparse representation of depth maps generated from stereo matching to reduce the residual error from INTER and INTRA predictions in depth coding. We provide a mathematical foundation for DHP-based lossless depth coding by theoretically analyzing its rate-distortion cost. Then, due to the mismatch between depth value and rendering position, there is a many-to-one mapping relationship between them in view synthesis, which induces the ADD model. Based on this ADD model and DHP, depth coding with lossless view synthesis quality is proposed to further improve the compression performance of depth coding while maintaining the same synthesized video quality. Experimental results reveal that the proposed DHP based depth coding can achieve an average bit rate saving of 20.66% to 19.52% for lossless coding on Multiview High Efficiency Video coding (MV-HEVC) with different groups of pictures. In addition, our depth coding based on DHP and ADD achieves an average depth bit rate reduction of 46.69%, 34.12% and 28.68% for lossless view synthesis quality when the rendering precision varies from integer, half to quarter pixels, respectively. We obtain similar gains for lossless depth coding on the 3D-HEVC, HEVC Intra coding and JPEG2000 platforms.

关键词： Encoding Image coding Three-dimensional displays Distortion Rendering (computer graphics) Solid modeling Bit rate lossless coding depth coding HEVC depth histogram projection allowable depth distortion view synthesis

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