Multiple Description Coding With Prediction Compensation

Sun, Guoqian; Samarawickrama, U.; Liang, Jie; Tian, Chao; Tu, Chengjie; Tran, Trac D.

doi:10.1109/tip.2009.2013068

Cited by 27 publications

(2 citation statements)

References 45 publications

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“…However, it is a nontrivial task to produce quantization noise with high negative correlation in practice [ 36 ]. There are some schemes that are able to achieve correlation that tends towards

[ 36 ], e.g., [ 37 , 38 , 39 , 40 ]. These schemes and many other MD coding schemes in general produce two descriptions with the desired correlation by direct operations on the source signal.…”

Section: Simulation Studymentioning

confidence: 99%

Zero-Delay Multiple Descriptions of Stationary Scalar Gauss-Markov Sources

Fuglsig

Østergaard

2019

Entropy

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In this paper, we introduce the zero-delay multiple-description problem, where an encoder constructs two descriptions and the decoders receive a subset of these descriptions. The encoder and decoders are causal and operate under the restriction of zero delay, which implies that at each time instance, the encoder must generate codewords that can be decoded by the decoders using only the current and past codewords. For the case of discrete-time stationary scalar Gauss-Markov sources and quadratic distortion constraints, we present information-theoretic lower bounds on the average sum-rate in terms of the directed and mutual information rate between the source and the decoder reproductions. Furthermore, we show that the optimum test channel is in this case Gaussian, and it can be realized by a feedback coding scheme that utilizes prediction and correlated Gaussian noises. Operational achievable results are considered in the high-rate scenario using a simple differential pulse code modulation scheme with staggered quantizers. Using this scheme, we achieve operational rates within 0.415 bits/sample/description of the theoretical lower bounds for varying description rates.

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“…However, it is a nontrivial task to produce quantization noise with high negative correlation in practice [ 36 ]. There are some schemes that are able to achieve correlation that tends towards

[ 36 ], e.g., [ 37 , 38 , 39 , 40 ]. These schemes and many other MD coding schemes in general produce two descriptions with the desired correlation by direct operations on the source signal.…”

Section: Simulation Studymentioning

confidence: 99%

Zero-Delay Multiple Descriptions of Stationary Scalar Gauss-Markov Sources

Fuglsig

Østergaard

2019

Entropy

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“…Another group of methods for multiple description coding use correlating transform are proposed in [3]- [6] and references therein. Recently Sun et al [7] proposed a technique for multiple description coding based on combining lapped transform, block level source splitting and linear prediction.…”

Section: Introductionmentioning

confidence: 99%

Iterative Soft Decoding of Multiple Description Image over Wireless Channel

Majumder¹,

Verma²

2014

JCC

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Motivated by recent results in multiple description image coding over wireless networks, we propose a scheme for transmission of multiple descriptions through hybrid packet loss and additive white Gaussian noise channel. Each description is coded into multiple bitstreams by applying SPIHT coding on wavelet trees along spatial orientations and each stream is further compressed using arithmetic code. Use of error resilient entropy coding (EREC) is proposed in literature for synchronization requirement of variable length codes, but EREC is not compatible with iterative soft-in soft-out decoding of arithmetic code at the receiver. We propose the application of EREC assisted by state and tail bits (ERECST) in conjunction with iterative decoding of arithmetic code at receiver for reconstructing the multiple description coded image over packet loss and Gaussian noise channel. Experimental results demonstrate that an additional gain of 7 dB in PSNR is obtained over existing scheme.

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