doi: 10.7763/IJCTE.2011.V3.306
Image Medical Compression by A new Architecture Optimization Model for the Kohonen Networks
M. Ettaouil
,
Y. Ghanou ,
K. El Moutaouakil ,
M. Lazaar
- Faculty of Science and Technology of Fez, University Sidi Mohammed ben Abdellah, City Fez, MOROCCO
Abstract
This paper presents a novel lossy compression scheme for medical images by a new architecture Optimization model for the Self-Organized Map (OSOM). Both neural networks for lossy compression scheme are comparatively examined: Kohonen map and OSOM. This new approach based on genetic algorithms to determine the optimal parameters of neural networks. In the compression process of the proposed method, the medical image is decomposed into blocks of 4×4 pixels. The numerical results assess the effectiveness of the theoretical results shown in this paper, and the advantages of the new modeling.
Keywords
- Image medical compression
- Vector Quantization
- Codebook
- Self-Organized Map
- Genetic algorithms
How to Cite
M. Ettaouil, Y. Ghanou, K. El Moutaouakil, and M. Lazaar, "Image Medical Compression by A new Architecture Optimization Model for the Kohonen Networks," International Journal of Computer Theory and Engineering, vol. 3, no. 2, pp. 204-210, 2011. https://doi.org/10.7763/IJCTE.2011.V3.306
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).