1. Infrared Dim and Small Targets Detection Method Based on Local Energy Center of Sequential Image
- Author
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Zhenming Peng, Xiangsuo Fan, Jianlin Zhang, Yongmei Huang, and Zhiyong Xu
- Subjects
020301 aerospace & aeronautics ,Article Subject ,Basis (linear algebra) ,Infrared ,business.industry ,lcsh:Mathematics ,General Mathematics ,General Engineering ,02 engineering and technology ,lcsh:QA1-939 ,Image (mathematics) ,0203 mechanical engineering ,lcsh:TA1-2040 ,0202 electrical engineering, electronic engineering, information engineering ,Preprocessor ,Clutter ,020201 artificial intelligence & image processing ,Computer vision ,Noise (video) ,Artificial intelligence ,lcsh:Engineering (General). Civil engineering (General) ,Anisotropy ,business ,Energy (signal processing) ,Mathematics - 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.
- Published
- 2017