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http://dx.doi.org/10.5909/JBE.2018.23.4.484

Uniform Motion Deblurring using Shock Filter and Convolutional Neural Network  

Jeong, Minso (Department of Electronics and Computer Engineering, Hanyang University)
Jeong, Jechang (Department of Electronics and Computer Engineering, Hanyang University)
Publication Information
Journal of Broadcast Engineering / v.23, no.4, 2018 , pp. 484-494 More about this Journal
Abstract
The uniform motion blur removing algorithm of Cho et al. has the problem that the edge region of the image cannot be restored clearly. We propose the effective algorithm to overcome this problem by using shock filter that reconstructs a blurred step signal into a sharp edge, and convolutional neural network (CNN) that learns by extracting features from the image. Then uniform motion blur kernel is estimated from the latent sharp image to remove blur in the image. The proposed algorithm improved the disadvantages of the conventional algorithm by reconstructing the latent sharp image using shock filter and CNN. Through the experimental results, it was confirmed that the proposed algorithm shows excellent reconstruction performance in objective and subjective image quality than the conventional algorithm.
Keywords
Deblurring; Convolutional Neural Network (CNN); Shock filter; Uniform Motion blur; Blind deconvolution;
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