An improved embedded zerotree wavelet image coding method based on coefficient partitioning using morphological operation

In recent years, wavelets have attracted great attention in both still imag e compression and video coding, and several novel wavelet-based image compr ession algorithms have been developed so far, one of which is Shapiro's emb edded zerotree wavelet (EZW) image compression algorithm. However, there ar e still some deficiencies in this algorithm. In this paper, after the analy sis of the deficiency in EZW, a new algorithm based on quantized coefficien t partitioning using morphological operation is proposed. Instead of encodi ng the coefficients in each subband line-by-line, regions in which most of the quantized coefficients are significant are extracted by morphological d ilation and encoded first. This is followed by using zerotrees to encode th e remaining space which has mostly zeros. Experimental results show that th e proposed algorithm is not only superior to the EZW, but also compares fav orably with the most efficient wavelet-based image compression algorithms r eported so far.