Share Email Print

Proceedings Paper

ENAS-RIF algorithm for image restoration
Author(s): Yang Yang; Zhen-wen Yang; Tian-shuang Shen; Bo Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

mage of objects is inevitably encountered by space-based working in the atmospheric turbulence environment, such as those used in astronomy, remote sensing and so on. The observed images are seriously blurred. The restoration is required for reconstruction turbulence degraded images. In order to enhance the performance of image restoration, a novel enhanced nonnegativity and support constants recursive inverse filtering(ENAS-RIF) algorithm was presented, which was based on the reliable support region and enhanced cost function. Firstly, the Curvelet denoising algorithm was used to weaken image noise. Secondly, the reliable object support region estimation was used to accelerate the algorithm convergence. Then, the average gray was set as the gray of image background pixel. Finally, an object construction limit and the logarithm function were add to enhance algorithm stability. The experimental results prove that the convergence speed of the novel ENAS-RIF algorithm is faster than that of NAS-RIF algorithm and it is better in image restoration.

Paper Details

Date Published: 30 November 2012
PDF: 8 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85581Z (30 November 2012); doi: 10.1117/12.999520
Show Author Affiliations
Yang Yang, Information Engineering Univ. (China)
Air Force Airborne Academy (China)
Zhen-wen Yang, Air Force Airborne Academy (China)
Tian-shuang Shen, Air Force Airborne Academy (China)
Bo Chen, Air Force Airborne Academy (China)

Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?