Fuzzy trellis vector quantization of images

Abstract

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 LBG 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 (/spl sim/0.8 dB gain), while being significantly less sensitive to initial codebooks using short training image sequences.