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Optical Engineering

Adaptive method for the detection of infrared small target
Author(s): Hao Ding; Huijie Zhao
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Paper Abstract

Background suppression is an important problem in infrared small target detection. The two-dimensional least mean square (TDLMS) filter is a widely used method, but its performance will decline when targets are embedded in a complex cluttered background. To fill the gap, variable step-size TDLMS, the neighborhood analysis technique, and the edge-directional TDLMS filter are developed but still cannot achieve a satisfying performance. Here, an adaptive method for background suppression is proposed. According to different characteristics of the pixels in homogeneous/target regions and inhomogeneous regions, two basic filters are first designed. Then a fuzzy edge estimation factor is introduced to combine them into a uniform framework, in which the two basic filters can be switched automatically to fit different kinds of pixels. Finally, a new mechanism to update and propagate the coefficients of the prediction window is constructed. It makes sure that the adaptive method works smoothly and reveals a potential to be implemented in parallel. The experimental results demonstrate that the proposed method achieves significant improvement in background suppression and detection performance.

Paper Details

Date Published: 18 November 2015
PDF: 10 pages
Opt. Eng. 54(11) 113107 doi: 10.1117/1.OE.54.11.113107
Published in: Optical Engineering Volume 54, Issue 11
Show Author Affiliations
Hao Ding, BeiHang Univ. (China)
Huijie Zhao, BeiHang Univ. (China)

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