Research On Fusion Methods Of Remote Sensing Images Based On The Contourlet Transform

Image fusion is an indispensable technique for image analysis and computer vision. Multi-remote sensor image fusion has attracted many attentions in remote sensing image processing area. It investigates how to integrate image information from different remote sensors, and generate new data which contains more information. Remote sensor image fusion is used in a wide range of military and civil applications.First of all, an approach for remote sensing image registration based on Contourlet transform and mutual information is proposed. Contourlet, as a new multi-scale analysis algorithm, is more appropriate for the analysis of the image edges such as curve and line characteristics than wavelet. Mutual information is a suited judgement rule of comparability and needn't to process images. This algorithm is fractionized gradually, maked the search process from coarse to fine, decreased the search space, and improved the registration accuracy.Secondly, an image fusion method based on Contourlet transform and regional features is proposed. When Contourlet transform is introduced to image fusion, the characteristics of original images are taken better and more information for fused image is obtained. The algorithm considers the function of low-frequency in fusion image, and enhances the whole effect. The experimental results show that the integrate resolution of the fused image is improved. Next, an image fusion method based on Contourlet transform, ICA (independent component analysis) and SVM (support vector machine) is proposed.ICA is a recently developed linear data analysis method, which could realize sparse coding of images and capture the essential edge structures of the image data. SVM is an algorithm based on structure risk minimizing principle, and has high generalization ability. ICA and SVM can avoid the drawbacks of the single fusion rule. The experimental results show that the approach is simple, effective, and can obtain better results than others.Finally, an image fusion method based on Contourlet transform and SVC (support vector clustering) is proposed. SVC is an unsupervised learning strategy. The algorithm based on SVC doesn't need the training stylebooks, so the fusion rules have less depend on original images. The experiment results prove that the effects based on SVC is easily controlled. And the judgement of element definition is more accurate.