Motion image restoration based on sparse representation and guided filter
by Hang Zuo; Liejun Wang
International Journal of Computing Science and Mathematics (IJCSM), Vol. 10, No. 6, 2019

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.

Online publication date: Mon, 09-Dec-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com