[1]YIN Danyan,WU Yiquan.The detection of a small infrared target based on gray prediction and chaotic PSO[J].CAAI Transactions on Intelligent Systems,2011,6(2):126-131.
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
6
Number of periods:
2011 2
Page number:
126-131
Column:
学术论文—机器感知与模式识别
Public date:
2011-04-25
- Title:
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The detection of a small infrared target based on gray prediction and chaotic PSO
- Author(s):
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YIN Danyan1; WU Yiquan1; 2
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1 School of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2 Science and Technology on Electrooptic Control Laboratory, Luoyang 471009, China
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- Keywords:
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detection of infrared small target; background suppression; gray prediction; fuzzy maximum entropy; chaotic particle swarm optimization
- CLC:
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TP18;TN911.73
- DOI:
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- Abstract:
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By analyzing the characteristics of a small target and the background of an infrared image, a detection method of an infrared small target based on gray prediction and chaotic particle swarm optimization (PSO) was proposed. First, the GM(1,1) model of gray system theory was adopted to predict the infrared image background in a time domain. The subtraction of the source image minus the predicted image gave the residual image. As a result, the background was suppressed and the target was enhanced. Then, a twodimensional histogram oblique segmentation method based on chaotic PSO and fuzzy maximum entropy was presented. The residual image was segmented by this method, leading to the detection of the small target. The experimental results show that the proposed method can significantly increase the detection probability of an infrared target to achieve longrange small target detection.