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Image Noise Elimination Using Evolutionary Algorithm | ||
| Engineering and Technology Journal | ||
| Volume 24, Issue 6, June 2005, Pages 644-650 PDF (763.24 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.30684/etj.24.6.3 | ||
| Author | ||
| Matheel Emad AL - Deen Abdulmunim | ||
| Applied Science Dept. University of Technology | ||
| Abstract | ||
| Abstract Evolutionary algorithms like Genetic Algorithms ( GA ) and Genetic programming ( GP ) are domain - independent problem solving approaches in which computer programs are evolved to solve , or approximately solve , problems . Learning methods for image denoising consist of minimizing a functional , which incorporates both the data and some penalty term . Choosing the penalty term to involve the total variation of the image has the advantage of cleaning speckles without smoothing out the edges . In this paper , our goal is to investigate the use of genetic algorithms to minimize the functional . | ||
| Keywords | ||
| Keywords: Evolutionary algorithms; image processing; noise removal | ||
|
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