JOURNAL ARTICLE

Error-resilient video coding using long-term memory motion-compensated prediction over feedback channel

Han Seung JungChang‐Su KimSang Uk Lee

Year: 2000 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 4067 Pages: 636-636   Publisher: SPIE

Abstract

The MC-DCT based video coding has been generally used for its efficiency and easy implementation, but it is very vulnerable in error-prone environments. In this paper, we present an error-resilient video coding using multiple reference frame, based on the long-term memory motion compensated prediction (LTMP), and an error concealment technique associated with the proposed technique. The rate- distortion optimization of the LTMP is extended in order to yield the improved error-resilience and error concealment capabilities. Also, the proposed algorithm confines effectively the temporal error propagation using the negative acknowledgement in feedback channel, in which the corrupted area by channel errors as well as the propagated is estimated and removed from the search region for the motion compensation. Thus, the proposed algorithm yields the similar performance to the forced intra update (FIU) method in terms of the PSNR, but avoids the abrupt increase in the bitrate, resulting in more efficient network utilization than the FIU. By the computer simulations, we shall demonstrate that the proposed technique provides an acceptable performance both subjectively and objectively in error-prone environments, as compared with the H.263 and LTMP, with or without the feedback messages.

Keywords:
Computer science Motion compensation Acknowledgement Coding (social sciences) Error concealment Error detection and correction Channel (broadcasting) Motion estimation Encoding (memory) Algorithm Computer vision Artificial intelligence Decoding methods Mathematics Telecommunications Statistics

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Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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