Lossy compression of individual signals based on string matching and one pass codebook design

This paper describes an effort to extend the Lempel-Ziv algorithm to a practical universal lossy compression algorithm. It is based on the idea of approximate string matching with a rate-distortion (R-D) criterion, and is addressed within the framework of vector quantization (VQ). A practical one pass algorithm for VQ codebook construction and adaptation for individual signals is developed which assumes no prior knowledge of the source statistics and involves no iteration. We call this technique rate-distortion Lempel-Ziv (RDLZ). As in the case of the Lempel-Ziv algorithm, the encoded bit stream consists of codebook (dictionary) updates as well as indices (pointers) to the codebook. The idea of “trading” bits for distortion in modifying the codebook will be introduced. Experimental results show that, for Gaussian sources as well as real images, RDLZ performs comparably, sometimes favorably, to static codebook VQ trained on the corresponding sources or images