Multi-source Image Fusion Technology And Application Research

Multi-source image fusion is an integrated information processing technology, which mainly aims to improve the reliability of images by processing the redundant information and the definition of images by processing complementary information among several images. In recent years, multi-source image fusion has become to a new important and useful technology in the field of image analysis and computer vision. This paper is mainly to discuss pixel-level multi-source image fusion technology.First, the background of research, basic concepts, development, internal and external application and researches of multi-source image fusion technology were introduced, the paper elaborated the fundamental principles and methods employed in pixel-level image fusion technology. Then the image enhancement, image edge detection, image registration and image fusion, which are the four steps of image fusion, have been researched. And put forth a combination of the subjective and objective evaluation criteria for image fusion performance and the effect of the fused images.Second, mainly researched the image transform methods and the image registration methods used commonly, gave the image registration process model, designed an improved image registration algorithm and obtained the transform parameter accurately, experiment results showed the method's validity and reliability.At last, on the base of analyzing of the image fusion methods between the pyramid decomposition transform and the wavelet decomposition transform, the image fusion method of four levels wavelet decomposition transform which has better information entropy and average gradient was selected, and the image fusion through the visible image, the infrared image and the multi-focus image were simulated by using area rules, experiment results, which criticized by the objective evaluation, showed the method's availability.In this paper, the multi-source image fusion experiment system was implemented with GUI technology in MATLAB, the image enhancement, image edge detection, image registration, image fusion and quality evaluation modules were designed and implemented.