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Error Resilient Scalable Compression Based On Distributed Video Coding

Frédéric Dufaux MultiMedia Signal Processing Group (MMSPG), Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland Touradj Ebrahimi MultiMedia Signal Processing Group (MMSPG), Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland Published in: ·Journal Image Communication archive Volume 24 Issue 6, July, 2009 Pages 437-451 Elsevier Science Inc. New York, NY, USA tableofcontents doi>10.1016/j.image.2009.02.011 2009 Article Bibliometrics ·Downloads (6 Weeks): n/a ·Downloads (12 Months): n/a ·Downloads (cumulative): n/a ·Citation Count: 2 Recent authors with related interests Concepts in this article powered by Concepts inError-resilient scalable compression based on distributed video coding Lossy compression In information technology, "lossy" compression is a data encoding method that compresses data by discarding (losing) some of it. The procedure aims to minimize the amount of data that needs to be held, handled, and/or transmitted by a computer. The different versions of the photo of the dog at the right demonstrate how much data can be dispensed with, and how the images become progressively coarser as the data that made up the original one is discarded (lost). morefromWikipedia Data compression In computer science and information theory, data compression, source coding, or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying marginally important information and removing it. morefromWikipedia Distributed computing Distributed computing is a field of computer science that studies distributed systems. A distributed system consists of multiple autonomous computers that communicate through a computer network. The computers interact with each other in order to achieve a common goal. A computer program that runs in a distributed system is called a distributed program, and distributed programming is the process of writing such programs. morefromWikipedia Cliff effect In telecommunications, the (digita

LinkedIn Reddit Download Full-text PDF Error-resilient Scalable Compression based on Distributed Video CodingArticle (PDF Available) in Signal Processing Image Communication 24(6):437-451 · July 2009 with 142 ReadsDOI: 10.1016/j.image.2009.02.011 1st Mourad Ouaret2nd Frederic Dufaux29.74 · Institut Mines-Télécom3rd Touradj Ebrahimi38.42 · École Polytechnique Fédérale de LausanneAbstractDistributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian–Wolf (SW) and Wyner–Ziv (WZ). In this work, a performance analysis of image and video coding schemes based on DVC is presented, addressing http://dl.acm.org/citation.cfm?id=1551333 temporal, quality and spatial scalability. More specifically, conventional coding is used to obtain a base layer while WZ coding generates the enhancement layers. At the decoder, the base layer is used to construct Side Information (SI) for the DVC decoding process. Initially, we show that the scalable DVC approach is codec-independent, which means that it is independent https://www.researchgate.net/publication/223928884_Error-resilient_Scalable_Compression_based_on_Distributed_Video_Coding from the method used to encode the base layer. Moreover, the influence of the base layer quality on the overall performance of the schemes is studied. Finally, evaluation of the proposed schemes is performed in both cases, with and without transmission errors. The simulation results show that scalable DVC has a lower compression efficiency than conventional scalable coding (i.e. scalable video coding and JPEG2000 for video and image, respectively) in error-free conditions. On the other hand, the DVC-based schemes show better error resilience as they outperform conventional scalable coding in error-prone conditions. More specifically, the Rate Distortion (RD) performance of the proposed schemes for image coding is compared with respect to Reed Solomon (RS) protected JPEG2000. While the latter exhibits a cliff effect as its performance dramatically decreases after a certain error rate, the performance of the DVC-based schemes decreases in a steady way with error rate increase.Discover the world's research10+ million members100+ million publications100k+ research projectsJoin for free FiguresEnlargeEnlarge Full-text (PDF)DOI: ·Available from: Frederic DufauxDownload Full-text PDF CitationsCitations9ReferencesReference

using Turbo Trellis Coded Modulation, VC(25), No. 1, January 2009, pp. xx-yy. Springer DOI 0804 BibRef Weerakkody, W.A.R.J., Fernando, W.A.C., Adikari, http://www.visionbib.com/bibliography/image-proc195dis.html A.B.B., Rajatheva, R.M.A.P., Distributed video coding of Wyner-Ziv frames using Turbo Trellis Coded Modulation, ICIP06(257-260). IEEE DOI 0610 BibRef Adikari, A.B.B., Fernando, W.A.C., Weerakkody, W.A.R.J., Arachchi, H.K., A Sequential Motion Compensation Refinement Technique for Distributed video coding of Wyner-Ziv frames, ICIP06(597-600). IEEE DOI 0610 BibRef Gehrig, N.[Nicolas], Dragotti, error resilient P.L.[Pier Luigi], Geometry-Driven Distributed Compression of the Plenoptic Function: Performance Bounds and Constructive Algorithms, IP(18), No. 3, March 2009, pp. 457-470. IEEE DOI 0903 BibRef Earlier: Distributed Compression of Multi-View Images using a Geometrical Coding Approach, ICIP07(VI: 421-424). IEEE DOI 0709 BibRef And: Distributed compression of the plenoptic error resilient scalable function, ICIP04(I: 529-532). IEEE DOI 0505Compression for network of cameras where adjacent cameras may have very similar images. BibRef Girod, B., Aaron, A.M., Rane, S., Rebollo-Monedero, D., Distributed Video Coding, PIEEE(93), No. 1, January 2005, pp. 71-83. IEEE DOI 0501 BibRef Pereira, F.[Fernando], Torres, L.[Luis], Guillemot, C.[Christine], Ebrahimi, T.[Touradj], Leonardi, R.[Riccardo], Klomp, S.[Sven], Distributed Video Coding: Selecting the most promising application scenarios, SP:IC(23), No. 5, June 2008, pp. 339-352. WWW Link. 0806Distributed Video Coding; Wyner-Ziv video coding; Application scenarios BibRef Guillemot, C.[Christine], Pereira, F.[Fernando], Torres, L.[Luis], Special issue on distributed video coding, SP:IC(23), No. 5, June 2008, pp. 337-338. WWW Link. 0806Introdution to the 5 papers. See individual papers. BibRef Ouaret, M.[Mourad], Dufaux, F.[Frédéric], Ebrahimi, T.[Touradj], Iterative Multiview Side Information for Enhanced Reconstruction in Distributed Video Coding, JIVP(2009), No. 2009, pp. xx-yy. DOI Link 0903 BibRef Ouaret, M.[Mourad], Dufaux, F.[Frederic], Ebrahimi, T.[Touradj], Err

 

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