vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff117a180000002b58030001000500 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).
A. Sreenivasa Murthy, K.N. Ramesh, Y.A. Mamatha
Bangalore University, India
SPIHT, DWT, Image Compression
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 5 , Issue: 2 , Pages: 932-936 )
Date of Publication :
November 2014
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