Thresholding wavelets for image compression

The paper addresses the problem of thresholding wavelet coefficients in a transform-based algorithm for still image compression. Processing data before the quantization phase is a crucial step in a compression algorithm, especially in applications which require high compression ratios. In the paper, after a review on the applications of wavelets to image compression, a new solution to the problem of an accurate choice of thresholds is presented. It is based on the concept of local contrast and exploits the localization properties of wavelets and a maximization of the entropy to find the optimal threshold for the wavelet coefficients. The results are compared with standard thresholding techniques which do not include considerations about local distribution of pixel information within the image. At the end, examples of compression are given, where the algorithm includes the complete processing of transform coefficients (thresholding, quantization and coding)