Abstract

in this paper, image deblurring and denoising are presented. The used images were blurred either with Gaussian or motion blur and corrupted either by Gaussian noise or by salt & pepper noise. In our algorithm, a discrete wavelet transform is used to divide the image into two parts. This partition will help in increasing the manipulation speed of images that are of the big sizes. Therefore, the first part represents the approximation coefficients, that a blur is reduced by using the modified fixed-phase iterative algorithm. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.

The article was added to IASJ on 2012-09-11

388 Total full text downloads since the date of addition