The Technical Research On Modeling And Performance Evaluation Of Electro-optical Imaging System

Theoretical modeling, imaging simulation, and performance evaluation of Electro-Optical imaging sensors are very important subjects and hot researches in electro-optical imaging technique fields. It can not only provide references for the optimizing design of electro-optical imaging system, but also predict the field performance in various scenarios. Hence, its study is of significance in both theoretical research and practical application.In this paper, focusing on the electro-optical imaging character, the methods of imaging simulation and performance evaluation are studied. Main works are achieved as follow:(1)The three-dimensional scene (visible, infrared, low-light-level) are generated utilizing the Multi-Creator and Vega software focusing on the radiometric character of the target and background. The emphasis is based on the description of 3-D terrain shape, the generation method for transitional electro-optical texture, and the segmenting method of lattice in DEM. (2) Imaging simulation and Modeling of electro-optical imaging system. According to basic parameters of electro-optical imaging system, such as Field-of-View, frame frequency, the gray conversion model of scene to imaging system output image is first derived. Then the degrade effects results from various modules of imaging system is simulated utilizing the modulation transfer function and 3-D noise model. Furthermore, an imaging simulation approach based on system level measurement parameters:signal transfer function, modulation transfer function, noise equivalent differential temperature, and noise equivalent background radiant is proposed, and simulation results are given.(3) Focusing on dynamic imaging character, three kinds of motion:linear motion, vibration, random jitter are modeled, respectively using numerical integration method. Furthermore, the effects of low frequency vibration parameters:vibration cycle, exposure period, the instant exposure, and vibration amplitude on imaging quality are mainly studied. Then the prediction methods for field performance are proposed for the imaging system based on the eye vision and machine vision. (4) According to the eye recognition process, an objective discrimination approach for predicting field performance is proposed utilizing improved BP neural network. Considering the field measure data, the functional relationship between image feature and the target discrimination probability is determined. (5) The concept of objective measure criteria of image quality is briefly illustrated. The performance evaluation functions of the four types of measure criteria:normalized minimum variance, fidelity, correlation, information rate are given respectively, and their relationship are analyzed theoretically. Focusing on the spatial and energetic resolution loss simulation image of electro-optical imaging system, the output results of objective measure functions is calculated and compared. And, the reasonable characterization of the objective measure function in performance evaluation is validated.