Image Compression Technique Using a Hierarchical Neural Network
This paper present a Resilient Backpropagation (RBP) algorithm based on hierarchical neural network for image compression. The proposed technique includes steps to break down large images into smaller blocks for image compression/ decompression process. Furthermore, a Linear Backpropagation (LBP) al...
| Main Authors: | , |
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| Format: | Article |
| Language: | Arabic |
| Published: |
Mosul University
2006-12-01
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| Series: | Al-Rafidain Journal of Computer Sciences and Mathematics |
| Subjects: | |
| Online Access: | https://csmj.mosuljournals.com/article_164055_02e9a9f3dccb1b35a52205c1cbe0dd89.pdf |
| Summary: | This paper present a Resilient Backpropagation (RBP) algorithm based on hierarchical neural network for image compression. The proposed technique includes steps to break down large images into smaller blocks for image compression/ decompression process. Furthermore, a Linear Backpropagation (LBP) algorithm is also used to train hierarchical neural network, and both training algorithms are compared. A number of experiments have been achieved, the results obtained, are the compression rate and Peak Signal to Noise Ratio of the compressed/ decompressed images which are presented in this paper. |
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| ISSN: | 1815-4816 2311-7990 |