Research On Infrared Dim Target Detection Under Complex Background

The detection of dim target is the core technique in infrared surveillance system (IRSS), which takes a significant role in national security safeguarding. Accordingly, in this thesis, profound analysis and discussion on the detection technique above, and several novel detection approaches and research ideas are proposed; with detailed descriptions on the design of weapon system form the angles of realization. Moreover, two networking composition on infrared search and tracking system are established, providing relevant basis for the construction of infrared surveillance systems.Based on the analysis from different points of view on query images of dim targets, several novel approaches on detection of dim target are put forward.Firstly, information entropy weighted by image variance is introduced to analyze the images above and describe image complexity, and substantial causes of the complexity features in classified regions are discussed, where based a novel image preprocessing method and a self-adaptive threshold acquisition method are constructed, so that the dim targets can be finally detected with self-adaptive threshold processing. Secondly, fuzzy classification theory is proposed to analyze the infrared query images above, regions with class feature vectors are classified and defined based on the grey distribution, and class similar coefficients are defined according to the fuzzy classification, so that the target detection is achieved by reserving a dim target class.Thirdly, the fuzzy classification method described above is extended with classification models re-definition, class kernels are accordingly defined combined with class feature vectors, and class similarity degrees are defined to merge classes, so that the problems on mis-classification caused by incomplete class regions included in images of infrared dim targets are solved, where based a novel approach on dim target detection is constructed; an algorithm diagram is given based on the generalization of the two fuzzy detection approaches above.In addition, based on the traditional approaches of background suppression, analysis are made on the causes of poor suppression performance, and for the first time, regional direction histograms are introduced into the fields of dim target detection, where based an improved background suppression approach is proposed. The principle of traditional background suppression approach is discussed, and then the causes of poor suppression performance on traditional background suppression approaches are obtained. Accordingly, improvements are proposed that regional background suppression should be conducted on the basis of the regional grey features in an image. And therefore, regional direction histograms are introduced for local grey classification, while general models and general background coefficient models are defined with LBP as the structure expression for each regional class, via which background coefficient models are modified to match each region of the query images, so that the improved suppression is achieved.From the angles of system realization, research on the construction and design of the dim target detection system is profoundly conducted, with the decryptions of hardware & software engineering design and development on real-time application. Moreover, two networking composition on infrared search and tracking system are put forward, providing some basis for practical system application.