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Proceedings Paper

Infrared dim small target segmentation method based on ALI-PCNN model
Author(s): Shangnan Zhao; Yong Song; Yufei Zhao; Yun Li; Xu Li; Yurong Jiang; Lin Li
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Paper Abstract

Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

Paper Details

Date Published: 24 October 2017
PDF: 9 pages
Proc. SPIE 10459, AOPC 2017: Optical Storage and Display Technology, 104590A (24 October 2017);
Show Author Affiliations
Shangnan Zhao, Beijing Institute of Technology (China)
Yong Song, Beijing Institute of Technology (China)
Yufei Zhao, Beijing Institute of Technology (China)
Yun Li, Beijing Institute of Technology (China)
Xu Li, Beijing Institute of Technology (China)
Yurong Jiang, Bejing Institute of Technology (China)
Lin Li, Bejing Institute of Technology (China)

Published in SPIE Proceedings Vol. 10459:
AOPC 2017: Optical Storage and Display Technology
Byoungho Lee; Yongtian Wang; Xiaodi Tan; Xiangping Li, Editor(s)

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