王吉晖, 王小微, 陈松林, 金伟其. 基于自然背景的热成像系统信息量评价方法[J]. 红外与激光工程, 2014, 43(3): 772-778.
引用本文: 王吉晖, 王小微, 陈松林, 金伟其. 基于自然背景的热成像系统信息量评价方法[J]. 红外与激光工程, 2014, 43(3): 772-778.
Wang Jihui, Wang Xiaowei, Chen Songlin, Jin Weiqi. Information quantity evaluation of thermal imaging systems based on nature background[J]. Infrared and Laser Engineering, 2014, 43(3): 772-778.
Citation: Wang Jihui, Wang Xiaowei, Chen Songlin, Jin Weiqi. Information quantity evaluation of thermal imaging systems based on nature background[J]. Infrared and Laser Engineering, 2014, 43(3): 772-778.

基于自然背景的热成像系统信息量评价方法

Information quantity evaluation of thermal imaging systems based on nature background

  • 摘要: 为了研究自然环境因素对热成像系统综合性能的影响,在MRTD 信道宽度热成像系统综合性能评价模型基础上,比对TTP 模型,引入自然背景噪声因子,构建了基于自然背景的热成像系统综合性能信息量评价模型,通过实验给出了自然背景噪声因子的确定方法,并建立了模型的归一化形式。以典型场景为例,通过实验分析了不同自然背景对热成像系统目标信息量获取的影响,并与TTP模型的分析结果进行比较,二者具有较好的一致性。实验表明基于自然背景的热成像系统综合性能信息量评价模型能够较好地反映自然背景复杂度对系统综合性能的影响,可以应用于系统性能评价。

     

    Abstract: In order to research the impact of nature environment on the synthesized performance of thermal imaging systems, a nature background noise factor was presented and introduced into MRTD-CW model comparing with Target Task Performance (TTP) model. An information quantity model based on MRTD-CW model with the nature background factor was proposed to evaluate the impact of nature environment on the synthesized performance of thermal imaging systems. The algorithm of the nature background noise factor was defined by experiments and the normalized form of the information quantity model with the nature noise factor was given. Taking typical scenes as examples, the impact of nature background noise on the synthesized performance of thermal imaging systems was analyzed by the information quantity model with nature background noise factor, and which was consistent with those of TTP model. Results show that the information quantity model with nature background noise factor can analyze the impact of nature background complexity on the synthesized performance of thermal imaging systems and can be applied to the evaluation of thermal imaging systems.

     

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