Effect of contrast threshold function correction on NVThermIP model

Abstract

With the innovation of infrared imaging technology, the performance evaluation of the infrared imaging system plays an indispensable role in the general technology. Therefore, the establishment of a comprehensive, scientific and reasonable performance evaluation model is a prerequisite for accurately predicting the performance of the imaging system, and is also an effective technology to design and develop the high performance imaging system. According to previous studies, in this paper we analyze the key problems that need to be solved urgently in the current research and the factors limiting the development of performance evaluation techniques. The main researches of this paper are as follows. 1) Through improving the deficiencies of the inherent physical effect evaluation methods, the accuracy and reliability of the performance evaluation model are enhanced. 2) In order to meet the needs of performance optimization design, the performance parameters provided by product design and production requirements must be selected correctly to achieve an organic combination of performance evaluation model and imaging system.The NVThermIP model, a widely used performance evaluation model, is slightly inadequate for guiding the optimization of the parameters of an infrared system. A more scientific and reasonable performance evaluation model is proposed in this paper, in which the contrast-threshold function of the system in the NVThermIP model is corrected by noise equivalent temperature difference based on the theory of the human-eye noise. By quantitatively analyzing the typical physical effects on infrared imaging system, the modeling theory and process of NVThermIP model are introduced in detail. The simulation results give a visual representation of evaluating the performance of an infrared imaging system. The limitations of the NVThermIP model used to guide the design and production of the system and the deficiencies of the early theoretical basis for system optimization design are analyzed. The noise equivalent temperature difference is introduced to revise and perfect the NVThermIP model combined with the theory of human eye noise. The accuracy of the newly proposed model is verified by two experiments. Experimental results show that the corrected model is more accurate in system prediction and can be used to guide the design of a new system.