Efficient rate allocation for progressive image transmission via unequal error protection over finite-state Markov channels
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This paper proposes a unified framework for addressing progressive image transmission over noisy channels based on the finite-state Markov channel (FSMC) model. FSMC models are simple yet general enough to model binary symmetric, Gilbert-Elliott, and fading channels. They allow error sequence analysis that facilitates quantifying the statistical characteristics of the embedded bitstreams transmitted over FSMC in closed form. Using a concatenation of rate-compatible puncturing convolutional code and cyclic redundancy check code for error protection, we use a concatenation of rate-compatible punctured convolutional code and cyclic redundancy check code for error protection, which results in an unequal error protection (UEP) system, and find (sub-)optimal rate allocation solutions for our setup. By mapping fading channels to FSMCs, the JSCC problem is thus solved without the burden of simulations using an image-dependent lookup table. Fast algorithms are proposed to search for the optimal UEP. Experiments on embedded image bitstreams over FSMCs confirm our analytical results. 2005 IEEE.
IEEE Transactions on Signal Processing
author list (cited authors)
Zhongmin Liu, .., Minyi Zhao, .., & Zixiang Xiong.