Embedded zerotree based image coding with low decoding complexity using linear and morphological filter banks

The problem of low bit rate image coding is addressed. The proposed approach is based on the embedded zerotree wavelet (EZW) algorithm. At high compression ratios, visually annoying artifacts appear in the reconstructed images using the original EZW algorithm. Hence, the first goal of this paper is to improve the visual quality of the coded pictures. The main distortion is due to the Gibbs phenomenon of the linear filter bank and appears as “ringing effect” in the reconstructed images. The ringing effect is shown to be considerably reduced by using asymmetrical filter banks. It can even be completely removed by means of a morphological subband decomposition. The major drawback of the morphological filter bank is the loss of textures at high compression factors. The second objective is to make an optimal use of the embedded bit stream by reducing the computational cost of the decoding process. A new decomposition is proposed which reduces drastically the computational load of the synthesis stage