Feature-Oriented Multiple Description Wavelet-Based Image Coding

Abstract

We address the problem of resilient image coding over error-prone networks where packet losses occur. Recent literature highlights the multiple description coding (MDC) as a promising approach to solve this problem. In this paper, we introduce a novel wavelet-based multiple description image coder, referred to as the feature-oriented MDC (FO-MDC). The proposed multiple description (MD) coder exploits the statistics of the wavelet coefficients and identifies the subsets of samples that are sensitive to packet loss. A joint optimization between tree-pruning and quantizer selection in the rate-distortion sense is used in order to allocate more bits to these sensitive coefficients. When compared with the state-of-the-art MD scalar quantization coder, the proposed FO-MDC yields a more efficient central-side distortion tradeoff control mechanism. Furthermore, it proves to be more robust for image transmission even with high packet loss ratios, which makes it suitable for protecting multimedia streams over packet-erasure channels.