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Home > Archive>Volume 38, Issue 4, 2019 >520-527. DOI:10.11972/j.issn.1001-9014.2019.04.019
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Detection of ship targets based on CFAR-DCRF in single infrared remote sensing images
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1.Shanghai Institute of Technical Physics of Chinese Academy of Sciences, Shanghai, 200083, China;2.Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083 China;3.University of Chinese Academy of Sciences, Beijing 10000, China

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Supported by National Key R&D Program of China，the Special Fund Of Innovation Project of Shanghai Institute of Technical Physics，Chinese Academic of Sciences.

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    Abstract:

    This paper focuses on the problem of low detection accuracy and low pixel image extraction accuracy of traditional small target detection and ship detection methods. An improved target detection algorithm based on constant false-alarm rate（ CFAR ）- dense conditional fandom fields （ DCRF）is proposed. The algorithm is based on the characteristics of small target and false alarm signal changes but different structural features. It uses the advantages of conditional fandom fields (CRF) multi-dimensional context (space, radiation) to achieve false alarm feature suppression, and introduces CFAR to improve the model and improve DCRF. Based on this model, experiments were performed under different conditions. The analysis results show that the algorithm can make full use of the global context information of the sea area, and can reduce the false alarm rate while maintaining a high detection rate.

    Reference
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SONG Wen-Tao, HU Yong, KUANG Ding-Bo, GONG Cai-Lan, ZHANG Wen-Qi, HUANG Shuo. Detection of ship targets based on CFAR-DCRF in single infrared remote sensing images[J]. Journal of Infrared and Millimeter Waves,2019,38(4):520~527

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History
  • Received:January 10,2019
  • Revised:May 28,2019
  • Adopted:March 12,2019
  • Online: September 06,2019
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