Edge-Aware Level Set Diffusion and Bilateral Filtering Reconstruction for Image Magnification

Huang, Hua, Zang, Yu, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884 and Qi, Chun 2009. Edge-Aware Level Set Diffusion and Bilateral Filtering Reconstruction for Image Magnification. Journal of Computer Science and Technology 24 (4) , pp. 734-744. 10.1007/s11390-009-9254-z

Full text not available from this repository.

Abstract

In this paper we propose an image magnification reconstruction method. In recent years many interpolation algorithms have been proposed for image magnification, but all of them have defects to some degree, such as jaggies and blurring. To solve these problems, we propose applying post-processing which consists of edge-aware level set diffusion and bilateral filtering. After the initial interpolation, the contours of the image are identified. Next, edge-aware level set diffusion is applied to these significant contours to remove the jaggies, followed by bilateral filtering at the same locations to reduce the blurring created by the initial interpolation and level set diffusion. These processes produce sharp contours without jaggies and preserve the details of the image. Results show that the overall RMS error of our method barely increases while the contour smoothness and sharpness are substantially improved.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	computer application - image magnification reconstruction - edge-aware level set diffusion - bilateral filtering
Additional Information:	This work is supported by the National Natural Science Foundation of China under Grant Nos. 60703003 and 60641002.
Publisher:	Springer
ISSN:	1000-9000
Last Modified:	18 Oct 2022 13:32
URI:	https://orca.cardiff.ac.uk/id/eprint/14241

Citation Data

Cited 3 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item