A finite adaptive neighborhood suppression algorithm based on singular value decomposition

Weijie Wang; Kan Ren; Guohua Gu; Qian Chen

doi:10.1117/12.2266702

10 February 2017 A finite adaptive neighborhood suppression algorithm based on singular value decomposition

Weijie Wang, Kan Ren, Guohua Gu, Qian Chen

Proceedings Volume 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016); 102500L (2017) https://doi.org/10.1117/12.2266702
Event: Fourth International Conference on Optical and Photonics Engineering, 2016, Chengdu, China

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.

Citation Download Citation

Weijie Wang, Kan Ren, Guohua Gu, and Qian Chen "A finite adaptive neighborhood suppression algorithm based on singular value decomposition", Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102500L (10 February 2017); https://doi.org/10.1117/12.2266702

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