Journal of Applied Sciences1812-56541812-5662Asian Network for Scientific Information10.3923/jas.2014.1618.1622RaajanN.R.VijayabhaskarP.V.M.ShivaG.MithunP.1220141414In this study, we present an algorithm of SPIHT to compress
an image using various wavelet filters by way of bior 4.4, Coif1, Daubechies
families, Sym 3 and rbio 4.4. Compression methods are important in telemedicine
applications to amply represent an image by decreasing the amount of bits per
pixel. Data storage requirements are reduced and transmission efficiency is
improved because of compressing the image. This algorithm is real and computationally
efficient in case of coding an image. In recent years, a technique to decompose
an image using wavelets has obtained a big deal of reputation. Apart from the
performance of good compression, we may obtain good quality of image even if
truncation of bit stream happened at any point of time. All the standard filters
of wavelet are used and the results are compared with two different images (Lena
and lifting body) in the encoding section. Bit rate versus PSNR simulation results
are tabulated with different wavelet filters. Finally Bi-orthogonal (bior 4.4)
filter of wavelet family given better results.]]>Munteanu, A., J. Cornelis, G. Van der Auwera and P. Cristea,1999Adams, M.D.,2002Antonini, M., M. Barlaud, P. Mathieu and I. Daubechies,1992Logashanmugam, E. and R. Ramachandran,2008Ding, J.R. and J.F. Yang,2008Sayood, K.,2000Venkateswaran, N. and Y.V.R. Rao,2007Pennebaker, W.B. and J.L. Mitchell,1992Shapiro, J.M.,1993Taubman, D.,2000Li, Z.N. and M.S. Drew,2004