A Study Of Image Fusion Algorithm Based On Multiwavelet

With the development of modern remote sensing technology, more and more multi-resolution, multi-temporal and multi-spectral remote sensing image data are provided by different kinds of remote sensing. To get a more correct, clear and complete knowing about the target, it is urgent for us to find a way to synthesize different kinds of image data. So the technology of image fusion appears. Image fusion is a kind of new fashioned, hot and knotty technology, which can be used in a wide range of applications.This paper firstly introduced the theories and methods for remote sensing image fusion and adopted an easy pretreatment method. Subsequently, it discussed conventional fusion methods: linearity average addition, HPF, PCA and IHS method. Since wavelet transform in image fusion has acquired better effects, this paper discussed the characters and theories of wavelet and demonstrated the common algorithms.Multiwavelet is an extension from wavelet theory,and has several particular advantages in comparison with scalar wavelets on image processing. So after researching the characteristics of multiwavelet it gave a fusion method based on multiwavelet, and the detailed progresses are as follows: firstly did thorough research on images'multiwavelet transform, then set up multiwavelet fusion algorithms and compared with wavelet fusion algorithms to show multiwavelet's superiority. Compared the fusion results among GHM, CL and Smooth multiwavelet and showed different multiwavelets have effects on results. Ameliorated the algorithm and brought forward gradient addition method which made results more better. Since IHS method is better in conventional methods and the IHS and RGB mode both have advantages, brought forward IHS multiwavelet algorithm in comparison with RGB multiwavelet algorithm. Theresults are distinct.At last, summarized the investigative fruits and brought forward fancies and prospects for the problem and unfinished work.