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7 March 2014 Image deblurring using the direction dependence of camera resolution
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Proceedings Volume 9020, Computational Imaging XII; 902010 (2014)
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
The blurring that occurs in the lens of a camera has a tendency to further degrade in areas away from the on-axis of the image. In addition, the degradation of the blurred image in an off-axis area exhibits directional dependence. Conventional methods have been known to use the Wiener filter or the Richardson–Lucy algorithm to mitigate the problem. These methods use the pre-defined point spread function (PSF) in the restoration process, thereby preventing an increase in the noise elements. However, the nonuniform degradation that depends on the direction is not improved even though the edges are emphasized by these conventional methods. In this paper, we analyze the directional dependence of resolution based on the modeling of an optical system using a blurred image. We propose a novel image deblurring method that employs a reverse filter based on optimizing the directional dependence coefficients of the regularization term in the maximum a posterior probability (MAP) algorithm. We have improved the directional dependence of resolution by optimizing the weight coefficients of the direction in which the resolution is degraded.
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Yukio Hirai, Hiroyasu Yoshikawa, and Masayoshi Shimizu "Image deblurring using the direction dependence of camera resolution", Proc. SPIE 9020, Computational Imaging XII, 902010 (7 March 2014);


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