摘要
随着新技术、新工艺以及新结构的不断应用，多光谱成像技术已成为目前红外成像系统领域的重要发展方向。新技术的引入在改善系统性能的同时，也使影响系统性能的因素发生了明显变化，非常有必要改进传统的系统性能表征方法以适应这种新型红外成像系统的性能表征和评价。
本论文主要在以下几方面进行了研究工作：
（1）针对三角方向鉴别（TOD）度量方法，以红外成像系统虚拟样机生成的三角形靶标仿真图像为基础，通过设计理论计算与实际测量相结合的实验方法，对人眼正确鉴别概率与视觉阈值信噪比之间的关系进行了研究，获得了一定显示亮度下，针对不同尺寸三角形的人眼正确鉴别概率与视觉阈值信噪比之间的定量对应关系。研究结果不仅可以修正单波段红外成像系统的TOD性能理论模型，而且为多光谱红外成像系统性能模型的建立提供了基础数据。
（2）根据多光谱成像系统的工作原理，以人眼视觉可感知信噪比为基础，建立了基于方程的多光谱红外成像系统TOD性能理论模型，给出了基于二维可鉴别阈值与目标角空间频率关系的系统级性能表征方法，研究了不同融合结构和策略对各通道输出信息的关联作用以及对系统性能的影响。利用此模型，提出了一种表征多光谱红外成像系统温差鉴别性能的阈值尺度，探讨了系统空间分辨性能、光谱分辨性能以及温差鉴别性能之间的相互制约关系。对计算结果进行分析获得的结论与文献中通过实验获得的结论一致，验证了模型的合理性。
（3）根据多光谱成像系统与单波段成像系统在鉴别现场目标过程中存在的差异，以所建立的系统TOD性能模型为基础，提出了一种预测多光谱红外成像系统作用距离的方法。并通过理论预测与基于仿真图像的测试实验结果进行对比表明了该方法的有效性。
（4）就多光谱图像背景杂波量化及其对系统探测性能的影响进行了初步研究。利用所构建的多光谱测试图像和主观目标获取性能实验统计结果，研究了不同杂波量化尺度的波段适用性；探讨了背景杂波与成像系统探测性能的关系，指出了多光谱系统探测性能模型的修正思路，为后续工作提供了条件。
With the increasing application of new technologies, processes and structures,multispectral imaging technology has become one of the most important developmenttrends in infrared imaging field. The utilization of new technologies leads to not onlyimprovement of system performance, but also the change of factors which affect thesystem performance. Hence, it is necessary to improve the traditional performancecharacterization method to satisfy the performance characterization and evaluation ofthe novel infrared imaging system (IRIS).
This paper mainly involves research in the following several aspects:
(1) For the requirement of triangle orientation discrimination (TOD) measurement,the relationship between correct discrimination probability of the human eye and visualthreshold signal-to-noise ratio (SNR) is studied through combing theoreticalcalculation with practical experiment. Based on the simulation images of trianglepatterns generated by an IRIS simulation model, relationship curves between these twovariables are yielded for different triangle angular subtenses (or sizes) with specifiedluminance, which is helpful not only to modify the existed single-band IRISperformance model but also to provide the basic data for the building of themultispectral IRIS performance model.
(2) According to the working mechanism of multispectral imaging system, basedon the visually perceivable SNR, a TOD performance theoretical model of amultispectral staring IRIS with human vision is developed. Specifically, themathematical equations for predicting the TOD threshold of the system with differentfusion architecture are derived, with emphasis on the impacts of fusion on thethreshold. It yields a two-dimensional threshold surface in a three-dimensional graphwith the reciprocal angular subtense, the spectral difference, and the temperaturedifference as ordinates. Furthermore, a figure of merit Q related to the TODtemperature differential thresholds is introduced to analyze the relation of thediscrimination performance of multispectral IRIS to the size and the spectral differenceof test pattern. The preliminary validation with the experiment results suggests that thismodel can provide a reasonable prediction of the performance for a multispectral IRIS.
(3) According to the difference between a multispectral IRIS and a single-bandIRIS in discrimining a field target, a new method for predicting the operating range of a multispectral IRIS is proposed by utilizing TOD performance model. The validationwith the experimental results with simulation images suggests that this approach canpredict the operating range of a multispectral IRIS efficiently.
(4) Background clutter characterization for multispectral images and the effect ofbackground clutters on the detection performance of a multispectral IRIS are studiedpreliminarily. The application range of existed background clutter metrics isinvestigated through using multispectral images and statistical results of targetacquisition experiments. Then, the relationship between background clutter and thedetection performance of an IRIS is discussed. And the train of thought is proposed onhow to modify the detection performance prediction model of a multispectral IRIS byclutter metrics.
引文
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