Image compression using zerotree and multistage vector quantization

Abstract

The embedded zerotree of the wavelet coefficient (EZW) algorithm has become an effective way of compressing images. The use of multistage vector quantizer (MSVQ) provides successive-approximation coding for vectors. A new algorithm is proposed that, provides good quality of reconstructed images at very low bit rates. The algorithm uses successive-approximation quantization of both scalars and vectors on the wavelet coefficients of the image. Successive-approximation quantization of scalars and vectors is done using EZW and MSVQ algorithms respectively. The EZW algorithm is applied to wavelet coefficients belonging to coarser level subbands and MSVQ is applied to vectors of wavelet coefficients belonging to finer level subbands. The proposed method further uses static Huffman coding to achieve more compression.