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Design and Implementation of EZW & SPIHT Image Coder for Virtual Images

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Author(s): Priyanka Singh & Priti Singh

Journal: International Journal of Computer Science and Security
ISSN 1985-1553

Volume: 5;
Issue: 5;
Start page: 433;
Date: 2011;
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Keywords: Image Compression | Embedded Zerotree Wavelet | Set Partitioning in Hierarchical Trees | CR | PSNR | MSE | BPP.

ABSTRACT
The main objective of this paper is to designed and implemented a EZW & SPIHT EncodingCoder for Lossy virtual Images. Embedded Zero Tree Wavelet algorithm (EZW) used here issimple, specially designed for wavelet transform and effective image compression algorithm. Thisalgorithm is devised by Shapiro and it has property that the bits in the bit stream are generated inorder of importance, yielding a fully embedded code. SPIHT stands for Set Partitioning inHierarchical Trees. The SPIHT coder is a highly refined version of the EZW algorithm and is apowerful image compression algorithm that produces an embedded bit stream from which thebest reconstructed images. The SPIHT algorithm was powerful, efficient and simple imagecompression algorithm. By using these algorithms, the highest PSNR values for givencompression ratios for a variety of images can be obtained. SPIHT was designed for optimalprogressive transmission, as well as for compression. The important SPIHT feature is its use ofembedded coding. The pixels of the original image can be transformed to wavelet coefficients byusing wavelet filters. We have anaysized our results using MATLAB software and wavelet toolboxand calculated various parameters such as CR (Compression Ratio), PSNR (Peak Signal toNoise Ratio), MSE (Mean Square Error), and BPP (Bits per Pixel). We have used here differentWavelet Filters such as Biorthogonal, Coiflets, Daubechies, Symlets and Reverse BiorthogonalFilters .In this paper we have used one virtual Human Spine image (256X256).

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