Multi-source Image Fusion Technology Research

Image fusion is an important technique for image analysis and computer vision,and Multi-source image fusion is popular and important. The purpose of image fusion is to fully use the complementary and redundant information in multi-source images,which comes from different sensors, and to generate new images in order to get more complete, objective and essential cognition for the same thing or target,and to produce more compete and more reliable description and decision than one image, in order that the fused image should be more suitable for human visual perception and computer further processing. With the rapid development of science and technology, the application of mufti-source image fusion has been extended from military field to civil field, such as resources classification and monitoring, medical treatment, mineral exploration,environment surveillance and so on. The major problem to be solved in this area is how to better implement technology of multi-source image fusion and its application. In this paper, we make research on the correlated technologies of multi-source image fusion. The main work is as follows:(1)Discuss multi-source image fusion concerning the purpose and significance, development history, research situation, the process analysis and sources of this topic.(2)Introduce the pretreatment work of image fusion, such as image enhancement, geometric transformation, image registration and so on.(3)Summary common methods and their characteristics of image fusion, and improve appropriately problems in the algorithm.(4)Analyse the subjective and objective evaluation method of image fusion, and propose new evaluation method based on weighted sum of the joint feature.(5)Propose image fusion based on improved K-means Clustering and Contourlet Transform, Max Energy and Contourlet Transform and improved Wavelet-Contourlet Transform,on the basis of introducing properties and principles of Contourlet Transform,and evaluate the experimental results by using the subjective, objective and weighted sum of the joint feature evaluation methods, and evaluation results show the effectiveness of above methods. (6)Show the image fusion method in the application of terrain classification, military reconnaissance and pathology detection through experiments.(7)Summary the full next and prospect for future research.