Research On Digital Image Process And Recognition For Detection And Classification In IR Imaging ATR System

Along with the widespread application of infrared imaging automatic target recognition(IR ATR) on precision weapon system, the technology of IR ATR and its equipments are being rapidly developed all over the world. To meet the demand of the national defense key advanced research project for military, some problems regarding the IR ATR system are deeply studied in this dissertation, and some valuable results are obtained which are summarized as follows:In view of the application of infrared focal-plane array device (IRFPA) in a large dynamic range, a noniniformity algorithm based on no linear fast Kalman filtering is proposed which can implement both nonuniformity and nonlinearity correction to IRFPA with less calculation. Aiming at the applications in some special environment of the inadequate scene change as well as the meet of system practical application, a correction algorithm based on stationary wavelet transform is presented which can be carried on under such circumstance.The infrared imagery is easy contaminated by noise in the transmission process, in addition the infrared imagery has the properties of blurring and Details unclear, which affect the accuracy of target detection and matching seriously. For this reason a new adaptive enhancement algorithm is proposed based on joint histogram equalization with image fusion, which can suppress noise and enhances the contrast effectively. Moreover new details is added by the use of nonlinear filter which enhances the detail while enhances the contrast. Aiming at the shortage of motion target edge blur caused by traditional frame accumulation SNR enhancement method, a new image enhancement algorithm is proposed based on image sequence. This algorithm can extract the motion field accurately of the target and then time-spatial filtering is applied to implement the image enhancement process. The validity of the method is validated by experimental results.Facing with difficulties of the infrared dim target detection in the condition of complicated background and low image SNR, a detection algorithm based on anisotropic judgment and bilateral filtering is presented. This algorithm can make an effective prediction of image background with subtle differences, and achieves a good suppression result. In view of the accurate Object Figure which IR ATR system needed, a fast two-dimension fuzzy entropy image segmentation algorithm based on ant colony algorithm is proposed. The formula of the fast two-dimension fuzzy entropy is derived, and then ant colony algorithm is employed to optimize the solving of the image threshold so that the object figure is extracted quickly and accurately.As the detection of infrared small target can be easily affected by various false target and random disturbance, a dual band infrared small target recognition algorithm is proposed based on fuzzy Dempster-Shafter evidence theory. The use of dual band infrared imaging overcome the shortage of single band imaging, and the combination of fuzzy sets theory and Dempster-Shafter evidence theory improves the recognition capability on obtained target information. Aiming at large target recognition, the application of wavelet moment invariant in infrared target recognition and its performance are deeply studied in this dissertation. This algorithm is able to recognize target with variations in size, position and orientation effectively. Experimental results show the superiority of the algorithm, and achieve satisfactory results.In addition, considering the application in complex battlefield environment, a high frame-rate IR ATR real-time signal processing system is also proposed, which can implement a series of algorithms that IR ATR system needed. This system has the advantage of high frame-rate, large dynamic range, high operation speed and precision, vigorous flexibility and versatility, etc.