| With the rapid pervade of Internet and transmission of image data, image compression becomes a hot research area. And because wavelet has a good locality in space and frequency domains, it is a useful tool to image compression.Wavelet transform coefficients are comprised by both a magnitude and a sign. While efficient algorithms exist for coding the transform coefficient magnitudes, current wavelet image coding algorithms are not as efficient at coding the sign of the transform coefficients.In this paper, sign coding is examined in detail in the context of an EZW image coder. In addition to using intraband wavelet coefficients in a sign coding context model, a projection technique is described that allows nonintraband wavelet coefficients to be incorporated into the context model. At the decoder, accumulated sign prediction statistics are also used to derive improved reconstruction estimates for zero-quantized coefficients. It will be shown that these techniques yield higher PSNR improvements. |
