Hamid A. Jalab and Rabha W. Ibrahim
Fractional Masks Based On Generalized Fractional Differential Operator for Image Denoising
308 - 313
2013
7
2
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/9996971
https://publications.waset.org/vol/74
World Academy of Science, Engineering and Technology
This paper introduces an image denoising algorithm based on generalized SrivastavaOwa fractional differential operator for removing Gaussian noise in digital images. The structures of nxn fractional masks are constructed by this algorithm. Experiments show that, the capability of the denoising algorithm by fractional differentialbased approach appears efficient to smooth the Gaussian noisy images for different noisy levels. The denoising performance is measured by using peak signal to noise ratio (PSNR) for the denoising images. The results showed an improved performance (higher PSNR values) when compared with standard Gaussian smoothing filter.
Open Science Index 74, 2013