A Fuzzy-SPIHT Image Compression Coding Algorithm Based on Human Visual System
Abstract: SPIHT (set partitioning in hierarchical trees) has given excellent results in terms of compression performance for majority images. However, it is not guaranteed to be optimal since the algorithm is not designed to explicitly consider the human visual system (HVS) characteristics. Extensive HVS research has shown that there are three perceptually significant activity blocks in an image: smooth, edge, and textured blocks. Since there is not an absolute limit between these image blocks, this paper presents Fuzzy-SPIHT algorithm, which embeds the HVS and fuzzy logic method into SPIHT. The algorithm is achieved by weighting wavlet coefficients sufficiently according to the fuzzy logic method and human visual sensitivity to these three blocks. By assigning perceptual weights accurately to the transform coefficients prior to SPIHT encoding thereby achieving higher perceptual quality and peak signal to noise ratio (PSNR) than the standard SPIHT especially at low bit rates.
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