Optimizing illumination concepts and calibration procedures for mid-wave infrared hyperspectral imaging

Mid-wave Infrared (MWIR) hyperspectral imaging reveals spectral characteristics of materials that are difficult or impossible to analyze in more commonly used spectral regions. However, challenges such as poor and unstable illumination, high cost, cooling requirements, and instability have limited its application in industry. This thesis focuses on optimizing the quality of raw MWIR hyperspectral data by designing a new line-focused illumination system using elliptical reflectors, refining the data acquisition process, and improving the calibration routine. These modifications resulted in an improved signal-to-noise ratio and in a more stable system. In addition, a detailed characterization of the camera was performed and the system stability was thoroughly evaluated.nnTo demonstrate the effectiveness of the improved system, its ability to classify black plastics - a critical task in waste recycling - was evaluated. These black plastics, which cannot be classified in other spectral regions due to low reflectivity caused by supplemented soot particles, were successfully distinguished using the optimized MWIR system.nnThe results indicate that while the revised hyperspectral imaging system shows potential for laboratory-based material classification, further improvements such as recalibration and environmental stabilization are needed for successful industrial use. n