DWT image compression using contextual bitplane coding of wavelet coefficients

Image coding using the discrete wavelet transform can attain very good results compared to traditional methods. In fact, most of the best known results for image coding have been related to the DWT. A simple scheme to code the DWT coefficients is the embedded zero-tree wavelet algorithm by Shapiro (1993). The embedded zero-tree wavelet can exploit both the similarity among subbands and the sparseness of the subbands. We propose a new simple image coder based on the DWT. The DWT coefficients are coded in bitplanes. Each bi-level pixel is coded in a context formed by its parental and surrounding pixels. In this way, both the similarity and the sparseness among subbands are exploited. We show the experimental results, both in terms of distortion measurement and visual comparison, and compare them to well-known methods