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Spectral imaging processing and gas identification based on FTIR imaging spectrometer

机译:基于FTIR成像光谱仪的光谱成像处理与气体识别

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Infrared spectral imaging has been used in many fields, such as gas identification, environmental monitoring and target detection. In practical application, it is difficult to classify the spectrum between target and background due to cluster background and instrument noise. This article introduces the design of a modular FTIR imaging spectrometer based on interference optics and accurate control module. Based on this instrument, a spectral feature analysis and gas identification method is proposed and verified via experiment. The exact steps and algorithms include radiometric calibration, spectral pre-process, and spectral matching. First, multiple-points linear radiometric calibration is indicated to improve the calibration accuracy. Secondly, the spectral pre-processing methods are realized to decrease the noise and enhance the spectral difference between target and background. Thirdly, spectral matching based on similarity calculation is introduced to realize gas identification. Three methods, Euclidean distance (ED), spectral angle mapping (SAM) and spectral information divergence (SID), are derived. Finally, an experimental test is designed to verify the method proposed in this article, where SF_6 is taken as the target. According to the results, various algorithms have different performance in time consumption and accuracy, and the proposed method is verified to be reliable and accurate in practical field test.
机译:红外光谱成像已用于许多领域,例如气体识别,环境监测和目标检测。在实际应用中,由于簇背景和仪器噪声,很难对目标和背景之间的光谱进行分类。本文介绍了基于干涉光学和精确控制模块的模块化FTIR成像光谱仪的设计。在此仪器的基础上,提出了一种光谱特征分析和气体识别方法,并通过实验进行了验证。确切的步骤和算法包括辐射校准,光谱预处理和光谱匹配。首先,指示多点线性辐射度校准以提高校准精度。其次,实现了光谱预处理方法,以减少噪声并增强目标与背景之间的光谱差异。第三,引入基于相似度计算的光谱匹配,实现气体识别。推导了三种方法,欧几里得距离(ED),光谱角映射(SAM)和光谱信息散度(SID)。最后,设计了一个实验测试来验证本文提出的方法,其中以SF_6为目标。根据结果​​,各种算法在时间消耗和准确性上都有不同的表现,并且在实际现场测试中证明了该方法的可靠性和准确性。

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