Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2017, Article ID 4572147, 16 pages
https://doi.org/10.1155/2017/4572147
Research Article

Infrared Dim and Small Targets Detection Method Based on Local Energy Center of Sequential Image

1Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
2School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu 610054, China
3University of Chinese Academy of Sciences, Beijing 100039, China

Correspondence should be addressed to Zhiyong Xu; moc.361@851yzx and Yongmei Huang; nc.ca.eoi@mygnauh

Received 19 February 2017; Revised 2 May 2017; Accepted 10 May 2017; Published 4 July 2017

Academic Editor: Aimé Lay-Ekuakille

Copyright © 2017 Xiangsuo Fan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In order to detect infrared (IR) dim and small targets in a strong clutter background, a method based on local energy center of sequential image is proposed. This paper began by using improved anisotropy for background prediction (IABP), followed by target enhancement by improved high-order cumulates (HOC). Finally, on the basis of image preprocessing, the paper constructs a sequential image energy center detection algorithm that integrates the neighborhood, continuity, area, and energy and other motion characteristics of the target. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HOC significantly increased the signal-noise ratio of images; when the signal-noise ratio (SNR) is lower than 2.5 dB, the proposed method could effectively eliminate noise and detect targets.