TY  - JOUR
T1  - Removal of Motion Blur Through Markov Random Field Model
AU - Sudhakar, R. AU - Amudha, J. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 1
SP  - 82
EP  - 89
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.82.89
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.82.89
KW  - multi-resolution
KW  -motion blur
KW  -Markov random field
KW  -image restoration
KW  -Deblurring
KW  -wavelet transform
AB  - This research study focuses on restoring images that are affected by motion blur which corrupts the image during acquisition. Restoration of images is an ill problem in image processing. A model derived from Markov Random Fields (MRF) is proposed to remove blur iteratively followed by best fit selector. Even then the blur components will be present in low frequencies. To reduce low frequency blur components, Discrete Wavelet Transform (DWT) is used and a second stage of MRF deblurring is done before the wavelet synthesis procedure. Experimental results shows better performance of the projected deblurring algorithm compared to other techniques in terms of image quality measures.
ER  -