Hagen Nathan
Department of Optical Engineering, Utsunomiya University, 7-2-1 Yoto, Utsunomiya 321-8585, Japan.
Sensors (Basel). 2025 Jan 17;25(2):538. doi: 10.3390/s25020538.
We describe the various steps of a gas imaging algorithm developed for detecting, identifying, and quantifying gas leaks using data from a snapshot infrared spectral imager. The spectral video stream delivered by the hardware allows the system to combine spatial, spectral, and temporal correlations into the gas detection algorithm, which significantly improves its measurement sensitivity in comparison to non-spectral video, and also in comparison to scanning spectral imaging. After describing the special calibration needs of the hardware, we show how to regularize the gas detection/identification for optimal performance, provide example SNR spectral images, and discuss the effects of humidity and absorption nonlinearity on detection and quantification.
我们描述了一种气体成像算法的各个步骤，该算法是为利用快照红外光谱成像仪的数据检测、识别和量化气体泄漏而开发的。硬件提供的光谱视频流使系统能够将空间、光谱和时间相关性整合到气体检测算法中，与非光谱视频相比，以及与扫描光谱成像相比，这都显著提高了其测量灵敏度。在描述了硬件的特殊校准需求后，我们展示了如何对气体检测/识别进行正则化以实现最佳性能，提供了信噪比光谱图像示例，并讨论了湿度和吸收非线性对检测和量化的影响。
