Asian Journal of Information Technology

Year: 2016
Volume: 15
Issue: 1
Page No. 82 - 89

Removal of Motion Blur Through Markov Random Field Model

Authors : J. Amudha and R. Sudhakar

Abstract: 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.

How to cite this article:

J. Amudha and R. Sudhakar, 2016. Removal of Motion Blur Through Markov Random Field Model. Asian Journal of Information Technology, 15: 82-89.

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