An efficient codebook post-processing technique and a window-based fast-search algorithm for image vector quantization

Vector quantization is an efficient image-coding technique to achieve a very low bit-rate compression. Furthermore, a lower bit rate can be achieved by equipping the vector quantizer with a memory unit or feedback loop so as to utilize the inter-vector correlation. For example, predictive vector quantization exploits the linear inter-vector correlation in the spatial domain by a linear vector prediction. Despite the better performance of this kind of vector quantizer, they are usually much more complex. In this paper, we proposed a simple but efficient codebook post-processing technique which enables the vector quantizer to possess a higher correlation preservation property. As is shown, the proposed post-processing technique leads to much higher inter-index correlation, of equivalently, smaller first-order (or higher order) entropy. Based on the special pattern of the codebook imposed by the post-processing technique, a window-based fast search (WBFS) algorithm is proposed. The WBFS algorithm not only accelerates the vector quantization processing, but also results in better rate-distortion performance