A Mini-Max Error Criterion Based Algorithm For Image Adaptive Vector Quantization

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Abstract
In this paper, we present a technique which employs the mini-max error criterion for image compression using adaptive vector quantization. In vector quantization (VQ), the image vectors are usually coded using an "universal codebook" generated from a set of training images. The coding performance using this codebook is potentially poor for images outside the training set. A number of inter and intra-image techniques have been proposed to adapt the codewords to the input image. However, these techniques do not guarantee the closest codewords to be within a prespecified bound of the input vectors. This can result in large errors which give rise to artifacts. We propose an intra-image adaptive technique which employs a criteria that minimizes the maximum error. Here, the codebook is generated on the fly from the input vectors to be coded. A primary codebook of size, 8 or 16 is typically used to store the frequently used codewords. A larger secondary codebook is used to store the less frequently used codewords. Both the transmitter and receiver maintain identical codebooks and hence keep track of any changes without any overhead information. As it is a single-pass technique, real-time implementation is possible.© (1989) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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