Fuzzy trellis vector quantization of images

This paper introduces a new codebook search algorithm for trellis vector quantization systems (TVQ). The development of the new algorithm is based on the symbol-MAP channel decoding algorithm, which is modified for data compression to deliver soft distortion-related reliability information. Following a rate-distortion theoretic approach, the soft information is used to derive a codebook search algorithm that is capable of solving the problems associated with the LEG algorithm. The derived algorithm is fuzzy in the sense that it follows a soft association rule, however, it is deterministic in the descent towards the global minimum distortion point. Although the derivation is general, the algorithm is tested using gray-scale images, which provide a nonconvex square-error distortion surface. As shown in the simulation section, the new algorithm provides lower energy codebooks (similar to 0.8 dB gain), while being significantly less sensitive to initial codebooks using short training image sequences.