Variable-coefficient fixed-length coding scheme for wavelet-based image communication over noisy channels

We propose in this paper a variable-coefficient fixed-length (VCFL) coding scheme for wavelet-based image transmission over noisy channels. When an image is transmitted through noisy channel with high throughput, both image compression and error-resistant coding scheme need to be considered. In this approach, an image is first decomposed into subbands by wavelet transform and quantized using an adaptive quantization scheme. The adaptive quantization is adaptive to both the frequency characteristics and the spatial constraints based on Gibbs random field. The traditional variable length entropy coding schemes, such as Huffman coding or arithmetic coding, and the fixed length coding such as LZW are usually very sensitive to channel noise for image transmission applications. Even with the insertion of synchronization symbols, they still cannot be directly employed without additional error correction/detection coding. To overcome the difficulty of image transmission over noisy channels, we propose to code the quantized subband coefficients with the VCFL scheme. This coding scheme attempts to keep the balance between redundancy removal, synchronization detection and error resilience. Part of the codebook is field based on the observation of the coefficient spatial distribution patterns in each subbands to alleviate the transmission of the codebook. The remaining code positions within the fixed length codebook can be utilized to combat channel errors by carefully arranging the code positions such that the codes with biggest transition cost will have the biggest Hamming distance. These positions can laos be filled with other frequently appeared coefficient composition sequences to achieve higher compression ratio. Experimental results of image transmission over noisy channels are reported to show the promising potential of the proposed coding scheme.