Subband vector quantization of images using hexagonal filter banks

Abstract Results of psychophysical experiments on human vision conducted in the last three decades indicate that the eye performs a multichannel decomposition of the incident images. This paper presents a subband vector quantization algorithm that employs hexagonal filter banks. The hexagonal filter bank provides an image decomposition similar to what the eye is believed to do. Consequently, the image coder is able to make use of the properties of the human visual system and produce compressed images of high quality at low bit rates. We present a systematic approach for optimal allocation of available bits among the subbands and also for the selection of the size of the vectors in each of the subbands.