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Image compression means reducing the size of graphics file, without compromising on its quality. Data compression is defined as the process of encoding data using a representation that reduces the overall size of data. This reduction is possible when the original dataset contains some type of redundancy. Digital image compression is a field that studies methods for reducing the total number of bits required to represent an image. This can be achieved by eliminating various types of redundancy that exist in the pixel values. The objective of this paper is to evaluate a set of wavelets for image compression. Image compression using wavelet transforms results in an improved compression ratio. Here in this paper we examined and compared Discrete Wavelet Transform Using wavelet families such as Haar,sym4, and Biorthogonal with Fast wavelet transform. In DWT wavelets are discretely sampled. The Discrete Wavelet Transform analyzes the signal at different frequency bands with different resolutions by decomposing the signal into an approximation and detail information. The study compares DWT and Advanced FWT approach in terms of PSNR, Compression Ratios and elapsed time for different Images. Complete analysis is performed at first, second and third level of decomposition using Haar Wavelet, Symlet and Biorthogonal wavelet. The implementation of the proposed algorithm based on Wavelet Transform. The implementation is done under the Image Processing Toolbox in the MATLAB

ADVANCE DIGITAL IMAGE COMPRESSION USING FAST WAVELET TRANSFORMS COMPARATIVE ANALYSIS WITH DWT