杨蔚, 顾国华, 陈钱, 曾海芳, 徐富元, 王长江. 红外偏振图像的目标检测方法[J]. 红外与激光工程, 2014, 43(8): 2746-2751.
引用本文: 杨蔚, 顾国华, 陈钱, 曾海芳, 徐富元, 王长江. 红外偏振图像的目标检测方法[J]. 红外与激光工程, 2014, 43(8): 2746-2751.
Yang Wei, Gu Guohua, Chen Qian, Zeng Haifang, Xu Fuyuan, Wang Changjiang. Method of target detection for infrared polarization image[J]. Infrared and Laser Engineering, 2014, 43(8): 2746-2751.
Citation: Yang Wei, Gu Guohua, Chen Qian, Zeng Haifang, Xu Fuyuan, Wang Changjiang. Method of target detection for infrared polarization image[J]. Infrared and Laser Engineering, 2014, 43(8): 2746-2751.

红外偏振图像的目标检测方法

Method of target detection for infrared polarization image

  • 摘要: 红外偏振成像探测通过对目标辐射和反射偏振态的探测,针对传统光学无法解决的问题,在目标检测方面取得高精度的结果,特别是在军事探测中,能够快速地将混杂在自然背景下的人造目标检测出来,以增强对目标的识别。偏振探测中所依据的强度、偏振度及偏振角信息反映出的不同物理特性,具有很强的冗余性和互补性。针对该特性,提出一种红外偏振图像的目标检测方法:首先使用Mean-Shift算法对红外图像和偏振度图像进行聚类处理;然后利用DS证据理论将聚类后的红外图像和偏振度图像中的物体信息充分结合,以区分目标与背景,达到目标检测的目的;最后通过仿真实验图像与小波融合图像结果的对比表明该算法的优势。

     

    Abstract: Infrared polarization imaging measurement can be used to obtain the polarization state in target radioactive and reflective detection. With this method, the problems that traditional photometry cannot solve can be settled, and high-precision results were obtained. Particularly, in the field of military detection, polarization measurement can be introduced to distinguish artificial target quickly from the natural background, and performed well in target identification. The intensity, degree and angle of polarization that used in polarization measurement can reflect different physical properties, and along with them, redundancy and complementarity are revealed seriously. In allusion to the character, a target detection method for infrared polarization image was proposed: firstly, Mean-Shift algorithm was employed to aggregate the infrared and polarized image. Secondly, the object information of clustered infrared and polarized image according to DC evidence theory were combined. In this case, the target can be distinguished from the background, so as to achieve the purpose of target detection. Finally, comparison of the consequence of experimental image and wavelet fusion image to demonstrate the superiority of the presented algorithm.

     

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