基于CFAR-DCRF红外遥感舰船单帧目标检测方法
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作者单位:

1.中国科学院上海技术物理研究所,上海200083;2.中国科学院红外探测与成像技术重点实验室,上海200083;3.中国科学院大学,北京10000

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基金项目:

国家重点研发计划 2017YFC0602103;中国科学院上海技术物理研究所创新专项 CX-55国家重点研发计划(2017YFC0602103),中国科学院上海技术物理研究所创新专项(CX-55)


Detection of ship targets based on CFAR-DCRF in single infrared remote sensing images
Author:
Affiliation:

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

Fund Project:

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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    摘要:

    针对红外舰船小目标图像复杂背景弱信号,虚警率较高且难以被精确检测的问题,提出了一种恒虚警率(Constant False-Alarm Rate,CFAR)-全连接条件随机场(Dense Conditional Random Fields,DCRF)舰船目标检测算法。该算法针对小目标与虚警信号变化特征相似但结构特征不同的特点,利用CRF的多维上下文(空间、辐射)表达的优势,实现虚警特征抑制,并引入CFAR对模型进行改进,提高了DCRF对于弱信号目标的检出能力,实现舰船小目标的精确检测与分割。实验结果表明,该算法能够充分利用海域的全局上下文信息,能够在保持较高检出率同时,有效降低虚警率,实现单帧端到端的小目标检测。

    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.

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宋文韬,胡勇,匡定波,巩彩兰,张文奇,黄硕.基于CFAR-DCRF红外遥感舰船单帧目标检测方法[J].红外与毫米波学报,2019,38(4):520~527]. 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]. J. Infrared Millim. Waves,2019,38(4):520~527.]

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  • 收稿日期:2019-01-10
  • 最后修改日期:2019-05-28
  • 录用日期:2019-03-12
  • 在线发布日期: 2019-09-06
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