A fast wavelet image coder based on contextual coefficient coding

We present a new image compression coder based on the discrete wavelet transform (DWT). We propose a new method to code the quantized wavelet coefficients. This way of coding exploits both the sparseness and the self-similarity amongst the subbands. By using contextual coding and a binary arithmetic coder, the statistics of the coefficients is automatically captured. The system is completely adaptive. It is also simple, fast and of low complexity. The proposed system is shown to have good performance, competitive with other more complicated methods. On Lena 512/spl times/512, a compression ratio (CR) of 103 can be attained with peak signal over noise ratio (PSNR) of 28.9 dB.