A Research On Multi-Source Image Fusion And Flow Modeling

As the important research branch in multi-source data fusion region, research on multi-source image fusion is how to obtain a new image with self-complementary and advantage information by combine different image data from different sensors together based on some fusion algorithm. The purpose is not only to overcome the limitation and the discrepancy of single image in geometry, spectrum and spatial resolution and then to increase image quality, but also to be good for the next application including target identification, feature extraction and change detection and so on. In this day with high-speed informationization development, multi-source image fusion technology has become an absolutely necessary technology in data fusion region, and also has paid important function in some military and civil regions.There are three basic elements for establishing a complete multi-source image fusion system, which are logical image fusion flow, effective fusion rule selection and integrated fusion performance evaluation criterion. The research work of this paper is just carried out according to these three basic elements, which are depicted as follows:1 Different levels and modes for multi-source image fusion are deeply discussed; image fusion methods based on spatial domain and transform domain of pixel level are classified and researched, and then their simulation are carried out. Based on the above analysis, the applicability and its boundary condition for each fusion method are analyzed;2 Existing evaluation criterions for image fusion are summarized, and the integrated evaluation system with four classes and twelve kinds standards including information quantity, statistic characteristics, signal-noise ratio and gradient value are presented, which can provide a quantitative evaluation criterion for image fusion; and then a new evaluation method for image fusion based on multi-factors criterions taking visual analysis as main measure and quantitative analysis as auxiliary measure is researched, and a close-loop evaluation system framework is presented, which can provide a theoretical supporting for next research;3 Based on the analysis for different image fusion method and fusion types, a modeling method on multi-source image fusion process is analyzed and researched, and moreover a closed image fusion process taking image data as input, fusion model and fusion rule as core, fused images as output and fusion appraisal system based on multifactor integrative criterion as terminal is presented, and finally, the validity of this fusion process is validated by relevant fusion experiments;4 In view of each fact of local deviation and high-pass filtering in image fusion and based on using wavelet transform to do image fusion, a new selection method for fusion rule is studied. Image fusion algorithm based on local deviation and high-pass filtering of wavelet transform is advanced. Taking the fusion between PAN image and multi-spectral image as example, the simulation results show that compared with the other single method, the new method presented is clearly better in preserving spectral and improving spatial presentation.