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A finite adaptive neighborhood suppression algorithm based on singular value decomposition
Author(s): Weijie Wang; Kan Ren; Guohua Gu; Qian Chen
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Paper Abstract

This paper proposes a finite adaptive neighborhood suppression algorithm based on singular value decomposition for small target detection in the infrared imaging system. The algorithm firstly does singular value decomposition on the whole gray image, selecting the larger singular values to reconstruct the image and achieving the purpose of noise suppression, thereby obtaining the image matrix contains only weak point of the target and its possible. Then, the pixels are divided into foreground and background in the fixed neighborhood followed by contrast enhancement. Experimental results show that this method can effectively preserve image details and the inhibiting effect is better.

Paper Details

Date Published: 10 February 2017
PDF: 6 pages
Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102500L (10 February 2017); doi: 10.1117/12.2266702
Show Author Affiliations
Weijie Wang, Nanjing Univ. of Science and Technology (China)
Kan Ren, Nanjing Univ. of Science and Technology (China)
Guohua Gu, Nanjing Univ. of Science and Technology (China)
Qian Chen, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10250:
International Conference on Optical and Photonics Engineering (icOPEN 2016)
Anand Krishna Asundi; Xiyan Huang; Yi Xie, Editor(s)

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