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Blurred image restoration using knife-edge function and optimal window Wiener filtering
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Blurred image restoration using knife-edge function and optimal window Wiener filtering
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Journal Article
Blurred image restoration using knife-edge function and optimal window Wiener filtering
2018
Overview
Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
