Title: Motion image restoration based on sparse representation and guided filter
Authors: Hang Zuo; Liejun Wang
Addresses: School of Information Science and Engineering, Xinjiang University, Urumqi Xinjiang 830046, China ' School of Information Science and Engineering, Xinjiang University, Urumqi Xinjiang 830046, China; School of Software and Engineering, Xinjiang University, Urumqi Xinjiang 830046, China
Abstract: When moving objects are present, current low-resolution blurring image reconstruction techniques with considerable noise do not perform well. This paper comes up with a new image reconstruction method based on K-SVD algorithm and guided filter technique. This method uses K-SVD to pre-process the image first and apply canny boundary detector to obtain clear boundaries as prior model, thus we can estimate blurring kernel. Last, we apply guided filter to reconstruct our image. We do the second and third step iteration to obtain clear images. This paper uses simulated degeneration and actual low-resolution blurring image for experiments and our result implies this method has good performance for reconstruction.
Keywords: image restoration; motion blur; K-SVD; edge detection; guided filter.
International Journal of Computing Science and Mathematics, 2019 Vol.10 No.6, pp.534 - 544
Received: 24 Jul 2017
Accepted: 25 Sep 2017
Published online: 09 Dec 2019 *