期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 52, 期 1, 页码 574-581出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2013.2242477
关键词
Derived kernel (DK); infrared (IR) image; local contrast; signal-to-noise ratio (SNR); target detection
类别
资金
- National Natural Science Foundation of China [61075116]
- Natural Science Foundation of Hubei Province [2009CDB387]
- Chinese National Basic Research 973 Program [2011CB302800]
- Macau Science and Technology Development Fund [008/2010/A1]
- Multi-Year Research of University of Macau [MYRG205(Y1-L4)-FST11-TYY, MYRG187(Y1-L3)-FST11-TYY]
- University of Macau [SRG010-FST11-TYY]
Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented in this paper. At the first stage, the local contrast map of the input image is obtained using the proposed local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. At the second stage, an adaptive threshold is adopted to segment the target. The experiments on two sequences have validated the detection capability of the proposed target detection method. Experimental evaluation results show that our method is simple and effective with respect to detection accuracy. In particular, the proposed method can improve the SNR of the image significantly.
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