Paper
30 November 2012 ENAS-RIF algorithm for image restoration
Yang Yang, Zhen-wen Yang, Tian-shuang Shen, Bo Chen
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Yang, Zhen-wen Yang, Tian-shuang Shen, and Bo Chen "ENAS-RIF algorithm for image restoration", Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85581Z (30 November 2012); https://doi.org/10.1117/12.999520
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image restoration

Detection and tracking algorithms

Image segmentation

Denoising

Image quality

Image processing algorithms and systems

Image filtering

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