19 April 2012 Universal deblurring method for real images using transition region
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Abstract
In this paper, we present a universal deblurring method for real images without prior knowledge of the blur source. The proposed method uses the transition region of the blurred image to estimate the point spread function (PSF). It determines the main edges of the blurred image with high edge measures based on the difference of Gaussians (DoG) operator. Those edge measures are used to predict the transition region of the sharp image. By using the transition region, we select the pixels of the blurred image to form a series of equations for calculating the PSF. In order to overcome noise disturbance, the optimal method based on the anisotropic adaptive regularization is used to estimate the PSF, in which the constraints of non-negative and spatial correlations are incorporated. Once the PSF is estimated, the blurred image is effectively recovered by employing nonblind restoration. Experimental results show that the proposed method performs effectively for real images with different blur sources.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Hanyu Hong, Hanyu Hong, Liangcheng Li, Liangcheng Li, Tianxu Zhang, Tianxu Zhang, In Kyu Park, In Kyu Park, } "Universal deblurring method for real images using transition region," Optical Engineering 51(4), 047006 (19 April 2012). https://doi.org/10.1117/1.OE.51.4.047006 . Submission:
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