Distributed Multiple Description Coding: Principles, by Huihui Bai, Anhong Wang, Yao Zhao, Jeng-Shyang Pan, Ajith

By Huihui Bai, Anhong Wang, Yao Zhao, Jeng-Shyang Pan, Ajith Abraham

The explosive development of community, multimedia and instant know-how is essentially altering the way in which humans converse, fueling call for for trustworthy real-time transmission of picture and video data.

This certain text/reference systematically examines the problems in allotted video coding (DVC) and a number of description coding (MDC), novel ideas designed to deal with the issues of traditional photo and video compression coding. The e-book starts off with a state of the art survey of the subject, earlier than featuring new equipment for making improvements to the functionality of photo and video transmission utilizing DVC and MDC. protecting all primary suggestions and center applied sciences, the chapters is also learn as self reliant and self-sufficient, describing each one technique in enough element to permit readers to copy the corresponding experiments easily.

Topics and features:

  • Provides a extensive review of DVC and MDC, from the elemental ideas to the newest research
  • Covers sub-sampling dependent MDC, quantization established MDC, remodel dependent MDC, and FEC established MDC
  • Discusses Sleplian-Wolf coding in line with faster and LDPC respectively, and evaluating relative performance
  • Includes unique algorithms of MDC and DVC
  • Presents the elemental frameworks and experimental effects, to aid readers increase the potency of MDC and DVC
  • Introduces the classical DVC approach for cellular communications, offering the developmental surroundings in detail

Researchers and engineers will locate this booklet an invaluable reference on DVC and MDC applied sciences, and a consultant for constructing useful purposes for DVC and MDC platforms. The textual content may also be of curiosity to graduate scholars in photo processing and sign processing.

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Additional info for Distributed Multiple Description Coding: Principles, Algorithms and Systems

Example text

We only need to transmit a few parity bits to restore X so that we can get higher compression. But something must be emphasized – this is not used as the forward error correction (FEC) to protect the error occurred during “effective channel” transmission but a source coding method to recover the primary information X by side information Y , assuming that there is a “virtual related noise channel” between X and Y . This method realizes the segmentation of the above codeword by the channel parity bits.

An MD image coder using pair-wise correlation transform is presented in [2]. A design of multiple-description scalar quantizers (MDSQ) for image coding is described in [3], which exploits a suboptimal algorithm to allocate rate subject to global constraints on the coding bit rate and side distortion. In [5], an MD image coding algorithm is developed also based on MDSQ with optimization of MDSQ parameters, which produces similar PSNR values with about 50–60% of the bit rates required by the two above-mentioned MD image coders.

Plenum, New York (1997) 12. : Mutiple description image coding using signal decompostion and reconstruction based on lapped orthogonal transforms. IEEE Trans. Circuits Syst. Video Technol. 9, 895–908 (1999) 13. : Lapped orthogonal transforms designed for error resilient image coding. IEEE Trans. Circuits Syst. Video Technol. 12, 752–764 (2002) 14. : Multiple description coding of motion fields for robust video transmission. IEEE Trans. Circuits Syst. Video Technol. 11, 999–1010 (2001) 15. : Reliable video communication over lossy packet networks using multiple state encoding and path diversity.

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