Image Coding Using Adaptive Wavelet Zerotree

Wavelet image decompositions generate a tree structured components that provide a hierarchical data structure for representing images. A new class of recently proposed image compression algorithms has focused on new ways for exploiting dependencies between this hierarchy of wavelet coefficients using zerotree data structures. This paper deals with a particular type of adaptive subband image coding where we focus on the image coder’s ability to adjust its coding length of each coefficient of high frequency subbands. Our model is inspired by a variation on the embedded zerotree wavelet (EZW). Our subband image coder based on the proposed adaptive quantization idea exhibits excellent rate-distortion performance. For popular test images, it is comparable or superior to most of the state-of-the-art coders in the literature. key words: image compression, discrete wavelet transform, EZW, P-zerotree.