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Joint Deblurring and Demosaicing Using Edge Information from Bayer Images
Du Sic YOO Min Kyu PARK Moon Gi KANG
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2014/07/01
Online ISSN: 1745-1361
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
deblurring, demosaicing, Bayer pattern, constraint least square, edge adaptive process,
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Most images obtained with imaging sensors contain Bayer patterns and suffer from blurring caused by the lens. In order to convert a blurred Bayer-patterned image into a viewable image, demosaicing and deblurring are needed. These concepts have been major research areas in digital image processing for several decades. Despite their importance, their performance and efficiency are not satisfactory when considered independently. In this paper, we propose a joint deblurring and demosaicing method in which edge direction and edge strength are estimated in the Bayer domain and then edge adaptive deblurring and edge-oriented interpolation are performed simultaneously from the estimated edge information. Experimental results show that the proposed method produces better image quality than conventional algorithms in both objective and subjective terms.