TY - JFULL AU - Hamid A. Jalab and Rabha W. Ibrahim PY - 2013/3/ TI - Fractional Masks Based On Generalized Fractional Differential Operator for Image Denoising T2 - International Journal of Computer and Information Engineering SP - 307 EP - 313 VL - 7 SN - 1307-6892 UR - https://publications.waset.org/pdf/9996971 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 74, 2013 N2 - This paper introduces an image denoising algorithm based on generalized Srivastava-Owa 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 differential-based 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. ER -