Open AccessRestoration of Noisy Blurred Images Using MFPIA and Discrete Wavelet Transform
Author(s) -
Dunia Tahir
Publication year - 2013
Publication title -
iraqi journal for electrical and electronic engineering/al-maǧallaẗ al-ʻirāqiyyaẗ al-handasaẗ al-kahrabāʼiyyaẗ wa-al-ilikttrūniyyaẗ
Language(s) - English
Resource type - Journals
eISSN - 2078-6069
pISSN - 1814-5892
DOI - 10.37917/ijeee.9.1.1
Subject(s) - deblurring , discrete wavelet transform , artificial intelligence , gaussian noise , mathematics , gaussian blur , computer vision , image restoration , wavelet transform , motion blur , noise (video) , wavelet , thresholding , salt and pepper noise , stationary wavelet transform , noise reduction , computer science , image (mathematics) , image processing , median filter
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, the modified fixed-phase iterative algorithm (MFPIA) is used to reduce the blur. Then a discrete wavelet transform is used to divide the image into two parts. The first part represents the approximation coefficients. While the second part represents the detail coefficients, that a noise is removed by using the BayesShrink wavelet thresholding method.