An infrared small target detection framework based on local contrast method |
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| Affiliation: | 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;2. Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA;3. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;4. Electronic Information School, Wuhan University, Wuhan 430072, China |
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| Abstract: | Small-target detection in infrared imagery used in forward looking infrared is an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate and speed. In this letter, a novel approach inspired by human visual system (HVS) is presented. First, block compressed sampling theory was used to compress the image and obtain the modulation map. Then, small abnormal regions in the modulation map were detected by high speed local contrast method and defined as candidate targets. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously. |
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| Keywords: | Small target detection Modulation map Human visual system High speed local contrast method Machine learning |
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