Image Compression and Filtering Operation Analysis using Integer Wavelet Transform

In image compression, the motive is to reduce the data redundancy significantly, both in spatial and frequency domain, without much affecting the quality of the picture. Almost lossless reversible image compression model is proposed for both continuous and discrete time cases, exploiting integer wavelet transform(IWT) employing lifting scheme(LS).Unlike its conventional counterpart in wavelet decomposition,here both approximation as well as detailed image contents are splitted providing better compression ratio. Both forward and inverse lifting schemes are exploited so as to reduce the computational complexity and achieve superior compression performance in terms of encoding time, decoding time, PSNR and better compression ratio(CR). Bi-orthogonal wavelets are constructed using lifting scheme that makes optimal use of both high pass and low pass filter values,with addition and shift operations to be performed on the resulting wavelet coefficients. This paper projects the robustness of IWT employing LS used in real time compression of images involving non smooth domains.