DocumentCode
2332895
Title
Identification of motion blur for blind image restoration
Author
Yitzhaky ; Kopeika, N.S.
Author_Institution
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
fYear
1995
fDate
7-8 March 1995
Abstract
Successful restoration of blurred images depends primarily on the knowledge we have about the degradation process parameters, i.e., the point spread function (PSF) of the blur and the noise statistics. In many blur types, such as uniform or sinusoidal motions, the most important parameter for proper identification of the PSF is the blur extent parameter. This parameter is the smear size in the blurred image of a point object in the original image. A new method for identification of the blur extent in an image, blurred by horizontal motion of the camera during the exposure time, is presented in this paper. The blur extent identification is accomplished given only the motion-blurred and noisy image. The identification approach here is based on the error characteristics due to the intentional use of inappropriate PSFs in the restoration process. The knowledge of the camera displacement permits high resolution image restoration when this parameter can relate to a specific PSF such as that characterizing linear motion or vibrations. Since the approach is not iterative the computing time is relatively short.
Keywords
identification; image restoration; motion estimation; optical transfer function; blind image restoration; blur extent parameter; camera displacement; error characteristics; identification; motion blur; noise statistics; point spread function; smear size; Additive noise; Autocorrelation; Convolution; Data mining; Discrete Fourier transforms; Image restoration; Layout; Optical noise; Shadow mapping; Wiener filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Electronics Engineers in Israel, 1995., Eighteenth Convention of
Conference_Location
Tel Aviv, Israel
Print_ISBN
0-7803-2498-6
Type
conf
DOI
10.1109/EEIS.1995.513832
Filename
513832
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