The University of British Columbia

Emerging wireless networks and multimedia developments are making compressed image transmission over noisy channels more widespread. However, most image compression algorithms have been developed without considering error robustness. While they are usually efficient in terms of compression, they are very sensitive to channel errors. In this paper, we propose a robust image compression algorithm based on lattice vector quantization where the dimension of the vector quantizer is matched to each processed subband in a wavelet based coder. The method also employs vector indexation in order to reduce or even eliminate the entropy coding stage, which is usually responsible for the poor performance of image coders in noisy environments. The proposed method yields compression performance levels similar to those achieved by the current JPEG-2000 standard verification model, but performs substantially better in terms of error resilience