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In this paper, we propose a low complexity lossless compression scheme for multispectral images based on distributed coding. Data decorrelation operations are moved to decoder on the ground in order to design a lightweight yet very efficient encoder suitable for onboard applications. The decoder with abundant resources will perform spectral-spatial adaptive fuzzy prediction to generate high quality...
In this paper, we investigate a fundamental issue in the distributed video coding (DVC) that, once resolved, would substantially improve the compression efficiency in DVC. This fundamental issue is the underlining relation between the distribution of the prediction errors and the compression efficiency of DVC. In the current approach to DVC, after the construction of prediction frame at decoder, the...
We present in this paper a novel distributed image coding scheme by exploiting image spatial correlation via Markov random field modeling at the decoding end. This allows us to design a simple yet efficient encoder suitable for various energy efficient imaging sensor network applications. The novelty is the integration of LDPC decoding and Markov random field modeling in order to jointly exploit both...
We present in this paper a novel distributed image coding scheme by exploiting image spatial correlation via Markov modeling at the decoding end. The exploitation of image statistics at the decoding end allows us to design a simple yet efficient encoder suitable for various energy efficient imaging sensor network applications. Existing distributed coding schemes developed for imaging sensor networks...
This paper presents a novel unequal error protection (UEP) video transmission scheme based on dynamic resource allocation in a MIMO-OFDM system in order to improve the video transmission performance over wideband wireless channels. In this new scheme, a low density parity code (LDPC) is combined with a complexity reduced power reallocation algorithm to utilize the excess powers which margin from the...
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