PERFORMANCE ANALYSIS OF SET PARTITIONING IN HIERARCHICAL TREES (SPIHT) ALGORITHM FOR A FAMILY OF WAVELETS USED IN COLOR IMAGE COMPRESSIONJournal: ICTACT Journal on Image and Video Processing (IJIVP) (Vol.5, No. 2)
Publication Date: 2014-11-01
Authors : A. Sreenivasa Murthy; K.N. Ramesh; Y.A. Mamatha;
Page : 932-936
Keywords : SPIHT; DWT; Image Compression;
With the spurt in the amount of data (Image, video, audio, speech, & text) available on the net, there is a huge demand for memory & bandwidth savings. One has to achieve this, by maintaining the quality & fidelity of the data acceptable to the end user. Wavelet transform is an important and practical tool for data compression. Set partitioning in hierarchal trees (SPIHT) is a widely used compression algorithm for wavelet transformed images. Among all wavelet transform and zero-tree quantization based image compression algorithms SPIHT has become the benchmark state-of-the-art algorithm because it is simple to implement & yields good results. In this paper we present a comparative study of various wavelet families for image compression with SPIHT algorithm. We have conducted experiments with Daubechies, Coiflet, Symlet, Bi-orthogonal, Reverse Bi-orthogonal and Demeyer wavelet types. The resulting image quality is measured objectively, using peak signal-to-noise ratio (PSNR), and subjectively, using perceived image quality (human visual perception, HVP for short). The resulting reduction in the image size is quantified by compression ratio (CR).
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Last modified: 2014-11-28 14:20:14