%0 Journal Article %1 Chaudhry:2007:IJIST %A Chaudhry, Asmatullah %A Khan, Asifullah %A Ali, Asad %A Mirza, Anwar M. %D 2007 %J International Journal of Imaging Systems and Technology %K SSIM, adaptive algorithms, filtering fuzzy genetic image index kriging, logic, measure, programming, punctual restoration, similarity spatial structure %N 4 %P 224--231 %R doi:10.1002/ima.20105 %T A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming %V 17 %X We present an intelligent technique for image denoising problem of gray level images degraded with Gaussian white noise in spatial domain. The proposed technique consists of using fuzzy logic as a mapping function to decide whether a pixel needs to be krigged or not. Genetic programming is then used to evolve an optimal pixel intensity-estimation function for restoring degraded images. The proposed system has shown considerable improvement when compared both qualitatively and quantitatively with the adaptive Wiener filter, methods based on fuzzy kriging, and a fuzzy-based averaging technique. Experimental results conducted using an image database confirms that the proposed technique offers superior performance in terms of image quality measures. This also validates the use of hybrid techniques for image restoration.

@article{Chaudhry:2007:IJIST, abstract = {We present an intelligent technique for image denoising problem of gray level images degraded with Gaussian white noise in spatial domain. The proposed technique consists of using fuzzy logic as a mapping function to decide whether a pixel needs to be krigged or not. Genetic programming is then used to evolve an optimal pixel intensity-estimation function for restoring degraded images. The proposed system has shown considerable improvement when compared both qualitatively and quantitatively with the adaptive Wiener filter, methods based on fuzzy kriging, and a fuzzy-based averaging technique. Experimental results conducted using an image database confirms that the proposed technique offers superior performance in terms of image quality measures. This also validates the use of hybrid techniques for image restoration.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Chaudhry, Asmatullah and Khan, Asifullah and Ali, Asad and Mirza, Anwar M.}, biburl = {https://www.bibsonomy.org/bibtex/2c537658326d287418ed08e6c1f67f062/brazovayeye}, doi = {doi:10.1002/ima.20105}, interhash = {972c75d7da26ce0c3d5f41b112a9ae6f}, intrahash = {c537658326d287418ed08e6c1f67f062}, issn = {1098-1098}, journal = {International Journal of Imaging Systems and Technology}, keywords = {SSIM, adaptive algorithms, filtering fuzzy genetic image index kriging, logic, measure, programming, punctual restoration, similarity spatial structure}, number = 4, pages = {224--231}, timestamp = {2008-06-19T17:37:35.000+0200}, title = {A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming}, volume = 17, year = 2007 }