MULTI TIMES IMAGES FUSION BASED ON WAVELET THEORY

Abstract. The development of new monitoring systems and the increasing interest of researchers in obtaining reliable measurements have leaded to the development of automatic monitoring moving objects. One way to ensure monitoring object is to use multi time's image fusion. Image fusion is a sub area of the more general topic of data fusion. Image fusion can be roughly defined as the process of combining multiple input images into an image, which contains the "relevant" information from the inputs. The aim of image fusion is to integrate complementary and redundant information from multiple images to create a composite that contains a better fused image than any of the individual source images. Main purpose of the former is to increase both the spectral and spatial resolution of images by combining multiple images.

In this paper we tried to use this theory for moving object tracking, so with the usage of multi images that are obtained in different times and combination of them with this theory we identify the path of movement of moving object so this result could help us to implement automatic systems that that could monitor objects automatically without human interventation.

So in this paper first we will discuss the principal of fusion and its famous method (wavelet theory) and all process that involved for doing a fusion process.