Video coding standards k. R. Rao, Do Nyeon Kim Springer 2014
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS)
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- SUBJECTIVE EVALUATON OF COMPRESSION ALGORITHMS AND STANDARDS
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS)Special Issue on Screen Content Video Coding and Applications Screen content video has evolved from a niche to a mainstream due to the rapid advances in mobile and cloud technologies. Real-time, low-latency transport of screen visuals between devices in the form of screen content video is becoming prevalent in many applications, e.g. wireless display, screen mirroring, mobile or external display interfacing, screen/desktop virtualization and cloud gaming. Today's commonly-used video coding methods, however, have been developed primarily with camera-captured content in mind. These new applications create an urgent need for efficient coding of screen content video, especially as the support of 4k or even 8k resolution begins to achieve mass market appeal. Screen content video coding poses numerous challenges. Such content usually features a mix of computer generated graphics, text, and camera-captured images/video. With their distinct signal characteristics, content adaptive coding becomes necessary. This is without mentioning the varied level of the human's visual sensitivity to distortion in different types of content; visually or mathematically lossless quality may be required for all or part of the video. Recognizing the demand for an industry standard for coding of screen content, the ISO/IEC Moving Picture Experts Group and ITU-T Video Coding Experts Group have since January 2014 been developing new extensions for HEVC. The Video Electronics Standards Association also recently completed a Display Stream Compression (DSC) standard for next-generation mobile or TV/Computer display interfaces. The development of these standards introduced many new ideas, which are expected to inspire more future innovations and benefit the varied usage of screen content coding. Besides coding, there are many other challenging aspects related to screen content video. For instance, in applications like screen mirroring and screen/desktop virtualization, low-latency video processing and transmission are essential to ensure an immediate screen response. In addition to real-time streaming technologies, these applications need a parallel-friendly screen encoding algorithm that can be performed efficiently on modern mobile devices or remote servers in the data center, and require, in certain use cases, the harmony of their computing resources, to keep the processing time to a minimum. At the receiver side, best-effort decoding with consideration for transmission errors, along with visual quality enhancement, is expected. Addressing these constraints requires research from multiple disciplines as is the case for other applications. The intent of this special issue is to present the latest developments in standards, algorithms, and system implementations related to the coding and processing of screen content video. Original and unpublished research results with topics in any of the following areas or beyond are hereby solicited. - Screen content video coding techniques and standards, e.g. HEVC extensions and DSC - Visually or mathematically lossless screen content video coding - Application-specific screen content coding, e.g. display stream or frame memory compression - Screen-content related pre/post-processing, e.g. resizing and post-filtering - Visual quality assessment for screen content video - Parallel-friendly, low-delay encoding optimization - Robust decoding with error and power control - Hardware/software/cloud-based screen codec implementations - Real-time, adaptive screen content transport over Internet or wireless networks - Design examples of novel screen content video applications, e.g. screen/desktop virtualization and cloud gaming - System performance analysis and characterization Important dates - Manuscript submissions due 2016-01-22 - First round of reviews completed 2016-03-25 - Revised manuscripts due 2016-05-13 - Second round of reviews completed 2016-07-08 - Final manuscripts due 2016-07-22
Wen-Hsiao Peng wpeng@cs.nctu.edu.tw National Chiao Tung University, Taiwan Ji-Zheng Xu jzxu@microsoft.com Microsoft Research Asia, China Jöern Ostermann ostermann@tnt.uni-hannover.de Leibniz Universität Hannover, Germany Robert Cohen cohen@merl.com Mitsubishi Electric Research Laboratories, USA S. – H. Tsang, Y. – L. Chan and W. – C. Siu, “Fast and Efficient Intra Coding Techniques for Smooth Regions in Screen Content Coding Based on Boundary Prediction Samples”, ICASSP2015, Brisbane, Australia, April. 2015. J. Nam, D. Sim and I.V. Bajic, “HEVC-based Adaptive Quantization for Screen Content Videos,” IEEE Int. Symp. Broadband Multimedia Systems, pp. 1-4, Seoul, Korea, 2012.
SE.2 H.R. Wu et al, “Perceptual visual signal compression and transmission”, Proc. IEEE, vol. 101, pp.2025-2043, Sept. 2013. SE.3 C. Deng et al (Editors), “Visual Signal Quality Assessment: Quality of Experience (QoE)”, Springer, 2015. SE.4 T.K. Tan et al, “Video Quality Evaluation Methodology and Verification Testing of HEVC Compression Performance”, IEEE Trans. CSVT, vol. 26, pp.76-90, Jan. 2016. Abstract of this paper is reproduced here for ready reference. Abstract— The High Efficiency Video Coding (HEVC) standard (ITU-T H.265 and ISO/IEC 23008-2) has been developed with the main goal of providing significantly improved video compression compared with its predecessors. In order to evaluate this goal, verification tests were conducted by the Joint Collaborative Team on Video Coding of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29. This paper presents the subjective and objective results of a verification test in which the performance of the new standard is compared with its highly successful predecessor, the Advanced Video Coding (AVC) video compression standard (ITU-T H.264 and ISO/IEC 14496-10). The test used video sequences with resolutions ranging from 480p up to ultra-high definition, encoded at various quality levels using the HEVC Main profile and the AVC High profile. In order to provide a clear evaluation, this paper also discusses various aspects for the analysis of the test results. The tests showed that bit rate savings of 59% on average can be achieved by HEVC for the same perceived video quality, which is higher than a bit rate saving of 44% demonstrated with the PSNR objective quality metric. However, it has been shown that the bit rates required to achieve good quality of compressed content, as well as the bit rate savings relative to AVC, are highly dependent on the characteristics of the tested content. This paper has many valuable references including subjective quality assessment methods recommended by ITU-T. SE5 J.-S. Lee and T. Ebrahimi, “Perceptual video compression: A survey,” IEEE J. Selected Topics on Signal Process., vol. 6, no. 6, pp. 684–697, Oct. 2012.
SE7 W. Lim and J.C. Kuo, “Perceptual video quality metric: a survey”, J. VCIR, vol.22, pp.297-312, 2011. SE8 F. Zhang and D.R. Bull, “A Perception-based Hybrid Model for Video Quality Assessment “, IEEE Trans. CSVT, (EARLY ACCESS) SE9 Y. Li et al, "No-reference image quality assessment using statistical characterization in the shearlet domain." Signal Processing: Image Communication, vol. 29, pp.748-759, July 2014. SE10 Y. Li et al, "No reference image quality assessment with shearlet transform and deep neural networks." Neurocomputing, vol.154, pp. 94-109, 2015. SE11 Y. Li et al, "No Reference Video Quality Assessment with 3D Shearlet Transform and Convolutional Neural Networks." IEEE Trans. on Circuits and Systems for Video Technology, 2015 ( early access) SE12 Y. Li,"No-reference image quality assessment using shearlet transform and stacked auto encoders," IEEE ISCAS, pp. 1594-1597, May 2015..
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