{"id":6168,"date":"2026-05-10T06:33:34","date_gmt":"2026-05-09T22:33:34","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=6168"},"modified":"2026-07-03T15:51:42","modified_gmt":"2026-07-03T07:51:42","slug":"space-time-based-detection-of-infrared-small-moving-target","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=space-time-based-detection-of-infrared-small-moving-target","title":{"rendered":"Space-time-based Detection of Infrared Small Moving Target"},"content":{"rendered":"\n
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<\/i> 2020<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 23, Issue 3<\/a><\/p>\n<\/div>\n\n\n\n

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Wencheng Wu1<\/sup> and Askar Hamdulla1<\/sup><\/i><\/a><\/p>\n\n\n\n

1<\/sup>Institute of Information Science and Engineering, Xinjiang University, Urumqi 830046, China<\/p>\n<\/div>\n\n\n\n

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Received:\u00a0May 15, 2019
Accepted:\u00a0May 10, 2020
Publication Date:\u00a0May 10, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Example of target enhancement by morphological filtering of a base sample. (a) Original image. (b) \u03b4expansion<\/sub> \u00b7 (c) \u03b4corrosion<\/sub> \u00b7 (d) fing\u2019<\/sub>.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202009_23(3).0014<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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With the development of infrared monitoring and early warning system, more and more attention has been paid to the research of infrared small target detection. How to effectively detect the target in a complex background has always been a major challenge for researchers. This paper presents a space-time-based detection for small infrared target, which can improve the performance of infrared small target detection system. Firstly, the targets are enhanced and the background clutter is suppressed by the morphological filter. Then, the segmentation images method is proposed to erase the majority noises, which calculates an adaptive thresholds based on the constant false alarm rate (CFAR). Finally, a dynamic detection is proposed to erase all of the noises in the multi-frame, which adjust the size and position of the search window based on the kinematic rule of targets. Experimental results show that this technology can effectively detect the small infrared target with high performance.<\/p>\n\n\n\n

Keywords:\u00a0Morphology filter; Constant false alarm rate CFAR; Motion feature analysis; Point target detection; SNR of point target<\/em><\/p>\n\n\n\n

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