Performance Test Of Portable Imaging Spectrometer

Imaging spectrometer is designed to capture image and spectral information of an object simultaneously, which is the great achievement combined with spectral and imaging technology. It is widely used in evidence examination, safety testing, agriculture, geological exploration and other related fields. As the more and more widely application for Imaging Spectrometer in various fields, the new requirements for the design principle of imaging spectrometer, the manufacture and the whole machine performance testing are put forward recently in the miniaturized and portable imaging spectrometer as a new trend of development.The research of performance test and methods for the portable spectrometer plays an important role in the development and application. Software and hardware compatibility, stability of the system and its main specifications determine the performance of portable imaging spectrometer. The content of the thesis is concentrated on portable imaging spectrometer performance testing. Firstly, a testing scheme basing on the principle, structure and functions of the portable imaging spectrometer is presented. The scheme consists of hardware and software testing plan and major technical indicators test plan. According to principles and functions of the portable imaging spectrometer, the test principles, test methods and testing process of its software and hardware is discussed. The main technical indicators test contains spectral transmittance test, spectral resolution test, spatial resolution test and the viewing angle test and so on. Secondly, in the thesis Matlab GUI design used for calculation and graphics analyzing of all test data with its function of data analysis and image processing is also discussed. Finally, an objective evaluation for both monochrome images and composite color image quality of the portable imaging spectrometer is given according to information entropy, image to the correlation coefficient, the image gray value standard deviation value and the average gradient of image gray value.