From Event: SPIE Optical Engineering + Applications, 2016
In image restoration problems it is commonly assumed that image degradations are linear. In real-life this assumption is not always satisfied causing linear restoration methods fail. In this work, we present the design of an image restoration filtering based on genetic programming. The proposed filtering is given by a secuence of basic mathematical operators that allows to retrieve an undegraded image from an image degraded with noise. Computer simulations results obtained with the proposed algorithm in terms of objective metrics are analyzed and discussed by processing images degraded with noise. The obtained results are compared with those obtained with existing linear filters.
José Enrique Hernández-Beltrán, Víctor H. Díaz-Ramírez, Leonardo Trujillo, and Pierrick Legrand, "Restoration of degraded images using genetic programming," Proc. SPIE 9970, Optics and Photonics for Information Processing X, 99700K (Presented at SPIE Optical Engineering + Applications: August 29, 2016; Published: 14 September 2016); https://doi.org/10.1117/12.2237092.
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