Frame based redundant-macro-block error resilient in scalable video coding

Jiung Liang Lin, Chih Hung Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a redundant macro block coding with texture-based selective boundary matching algorithm (RMB-TSBMA) is introduced to improve the video quality. Different from texture-based selective boundary matching algorithm (TSBMA), the algorithm is more suitable for frame based recovery. The RMB coding encodes the information of some essential blocks. When a frame gets lost, we can first decode RMBs, and then neighboring MBs with TSBMA, so that the RMBs can provide the correct position for boundary matching to get better visual quality. The influences of the RMB number, and the reordering method are also discussed. Compared to the other algorithms, the proposed RMB-TSBMA performs better than conventional method of temporal direct mode (TDM) by over 3dB PSNR at the packet loss rate 10%.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing, PCM 2010 - 11th Pacific Rim Conference on Multimedia, Proceedings
Pages372-381
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2010 Nov 9
Event11th Pacific Rim Conference on Multimedia, PCM 2010 - Shanghai, China
Duration: 2010 Sep 212010 Sep 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6298 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th Pacific Rim Conference on Multimedia, PCM 2010
CountryChina
CityShanghai
Period10-09-2110-09-24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lin, J. L., & Kuo, C. H. (2010). Frame based redundant-macro-block error resilient in scalable video coding. In Advances in Multimedia Information Processing, PCM 2010 - 11th Pacific Rim Conference on Multimedia, Proceedings (PART 2 ed., pp. 372-381). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6298 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-15696-0_35