Effect of wavelet filters on SFQ encoder performance for medical images

This paper is focused on analysing the effect of wavelet filters on Space frequency quantization (SFQ) coder performance. SFQ is a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation [1]. It has been shown that the statistics of wavelet coefficients in the medical images can be better approximated by the Generalized Pareto distribution (for positive DWT coefficients) and Generalized Student-t distribution (for negative DWT coefficients) [2]. To analyze the performance of SFQ coder with different wavelet filters PSNR (peak signal to noise ratio) is measured at various compression rates.