Infrared Small Target Detection Technology Research

With the rapid development of the infrared image technology and its wide prospect in the military application, the study on detecting small targets in the infrared detecting system have a great significance and practical value in enhancing the viability of the local warning system and effective counterattack capability as well as scramble for the mastery of the sky in the future wars. Meanwhile, it can be regarded as an important reference for the further improvement of arms guided technology such as the infrared image guided missile.In order to detect small targets, methods like multi-frame accumulation, threshold partition, median filtering, wavelet transformation, morphology filtering and background prediction are commonly applied. Among these methods, multi-frame accumulation can effectively control noise interference and improve the detecting efficiency and capability as a result of utilizing the movement of targets. However, this method is limited in application for its long accumulation, tremendous calculation and its requirement for the rate of moving targets. All the other four methods also shows their advantages and disadvantages such as threshold partition with simple arithmetic and fast speed as well as low efficient detecting. Therefore any ideal method is yet to be set up in application. The main contents of this dissertation are shown as follows:1. The arithmetic of background prediction based on the Judge Model is put forward after analyzing and comparing current typical infrared targets detecting arithmetic. It can automatically exclude the noise points deflecting from the true value in the predicting window so as to reduce the influence of the noise and background fluctuation on the background prediction. This can solve the problem of marginal ambiguity presented in the traditional predicting arithmetic as well as efficiently resist noise, especially in the blank background with complex cloud layers. Therefore, it is an important extension of the background predicting arithmetic and demonstrates favorable simulation.2. In the process of erasing background, twice predicting difference on the basis of double predicting windows is advanced so that the verifying noises in the poor...