Context based multiple bitstream image transmission over noisy channels

In this paper, we propose a novel combined source and channel coding scheme for image transmission over noisy channels. The main feature of the proposed scheme is a systematic decomposition of image sources so that unequal error protection can be applied according to not only bit error sensitivity but also visual context importance. The wavelet transform is adopted to hierarchically decompose the image. The association between the wavelet coefficients and what they represent spatially in the original image is fully exploited. Such decomposition generates wavelet blocks that can be classified based on their corresponding image context. The classification produces wavelet trees in each class with similar context and statistics and therefore enables high performance source compression using SPIHT. The channel coding assigns unequal error protection to different classes and to different bit planes so that the image transmission scheme is robust in terms of both subjective and objective visual quality. To further improve the quality of the received image, a post-processing method was proposed to restore the degradation due to the channel decoding residual error. Experimental results show that the proposed scheme has a good performance for image transmission over noisy channels. In particular, the reconstructed images consistently illustrate better visual quality.