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| Image Processing Compression and Reconstruction by
Using New Approach Artificial Neural Network
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Download
Complete Issue PDF(9.16MB) |
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Volume: 6 Issue: 2 |
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Pages: |
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Publication
Date: April 2012 |
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ISSN
(Online): 1985-2304 |
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Pages |
68 - 85 |
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Author(s) |
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Published
Date |
16-04-2012 |
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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: Artificial Neural Network, Multilayer Perception, Radial Basis Functions |
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| In this paper a neural network based image compression method is presented. Neural
networks offer the potential for providing a novel solution to the problem of data compression by its ability to generate an internal data representation. This network, which is an application of back propagation network, accepts a large amount of image data, compresses it for storage or transmission, and subsequently restores it when desired. A new approach for reducing training time by reconstructing representative vectors has also been proposed. Performance of the network has been evaluated using some standard real world images. It is shown that the development architecture and training algorithm provide high compression ratio and low distortion while maintaining the ability to generalize and is very
robust as well. |
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| K.Siva Nagi Reddy : Colleagues
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| B.R.Vikram : Colleagues
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| L. Koteswara Rao : Colleagues
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| B.Sudheer Reddy : Colleagues
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