Motion image restoration based on sparse representation and guided filter. (5th December 2019)
- Record Type:
- Journal Article
- Title:
- Motion image restoration based on sparse representation and guided filter. (5th December 2019)
- Main Title:
- Motion image restoration based on sparse representation and guided filter
- Authors:
- Zuo, Hang
Wang, Liejun - 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.
- Is Part Of:
- International journal of computing science and mathematics. Volume 10:Number 6(2019)
- Journal:
- International journal of computing science and mathematics
- Issue:
- Volume 10:Number 6(2019)
- Issue Display:
- Volume 10, Issue 6 (2019)
- Year:
- 2019
- Volume:
- 10
- Issue:
- 6
- Issue Sort Value:
- 2019-0010-0006-0000
- Page Start:
- 534
- Page End:
- 544
- Publication Date:
- 2019-12-05
- Subjects:
- image restoration -- motion blur -- K-SVD -- edge detection -- guided filter
Mathematics -- Periodicals
Computer science -- Periodicals
Mathematics -- Data processing -- Periodicals
510.285 - Journal URLs:
- http://www.inderscience.com/jhome.php?jcode=ijcsm ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 1752-5055
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 12013.xml