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| Design and Implementation of EZW & SPIHT Image Coder for Virtual Images
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Source |
International Journal of Computer Science and Security (IJCSS) |
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Volume: 5 Issue: 5 |
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Pages: NULL |
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Publication
Date: November / December 2011 |
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ISSN
(Online): 1985-1553 |
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433 - 442 |
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Author(s) |
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Published
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15-12-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Image Compression,, Embedded Zerotree Wavelet,, Set Partitioning in Hierarchical Trees, CR, PSNR, MSE |
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| The main objective of this paper is to designed and implemented a EZW & SPIHT Encoding Coder for Lossy virtual Images. .Embedded Zero Tree Wavelet algorithm (EZW) used here is simple, specially designed for wavelet transform and effective image compression algorithm. This algorithm is devised by Shapiro and it has property that the bits in the bit stream are generated in order of importance, yielding a fully embedded code. SPIHT stands for Set Partitioning in Hierarchical Trees. The SPIHT coder is a highly refined version of the EZW algorithm and is a powerful image compression algorithm that produces an embedded bit stream from which the best reconstructed images. The SPIHT algorithm was powerful, efficient and simple image compression algorithm. By using these algorithms, the highest PSNR values for given compression ratios for a variety of images can be obtained. SPIHT was designed for optimal progressive transmission, as well as for compression. The important SPIHT feature is its use of embedded coding. The pixels of the original image can be transformed to wavelet coefficients by using wavelet filters. We have anaysized our results using MATLAB software and wavelet toolbox and calculated various parameters such as CR (Compression Ratio), PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), and BPP (Bits per Pixel). We have used here different Wavelet Filters such as Biorthogonal, Coiflets, Daubechies, Symlets and Reverse Biorthogonal Filters .In this paper we have used one virtual Human Spine image (256X256). |
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| 1 |
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| Priyanka Singh : Colleagues
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| Priti Singh : Colleagues
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