Abstract
Image compression is the art of representing the image in a compact form rather than its original form. An image is a visual perception of a subject or surrounding. But digitally, it is an organization of minute building blocks called as pixels. In this paper the compression is done by two level processes, initially a Haar wavelet decomposition is applied then Adaptively Scanned Wavelet Difference Reduction Technique (ASWDRT) is done. The ASWDRT makes use of adaptive scanning order to estimate locations of new significant image values which leads to enhancement of edge resolution in compressed images. The performance measure of compression method is done with following parameters like Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Compression Ratio(CR). The quantitative evolution and comparison is done with some popular compression methods like Set Partitioning in Hierarchical Trees (SPIHT), Embedded Zero Tree Wavelet (EZW) and Wavelet Difference Reduction(WDR). The proposed method shows superior performance in terms of CR. The abovementioned Compression techniques are developed and performance parameters are calculated using MATLAB 2014.
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