A high-speed codebook design algorithm for ECVQ using angular constraint with search space partitioning

金沢大学大学院自然科学研究科情報システム金沢大学工学部In this paper, we propose a fast codebook generation algorithm for entropy-constrained vector quantization (ECVQ). The algorithm uses the angular constraint and employs a suitable hyperplane to partition the codebook and image data in order to reduce the search area and accelerate the search process in the codebook design. This algorithm allows significant acceleration in codebook design process. Experimental results are presented on image block data. These results show that our new algorithm performs better than the previously known methods

Fast Search Method for Image Vector Quantization Based on Equal-Average Equal-Variance and Partial Sum Concept

ABSTRACT The encoding process of image vector quantization (VQ) is very heavy due to it performing a lot of k-dimensional Euclidean distance computations. In order to speed up VQ encoding, it is most important to avoid unnecessary exact Euclidean distance computations as many as possible by using features of a vector to estimate how large it is first so as to reject most of unlikely codewords. The mean, the variance, L 2 norm and partial sum of a vector have been proposed as effective features in previous works for fast VQ encoding. Recently, in the previous wor