A kind of algorithm of image fusion based on NSCT

The NSCT is a complete shift-invariant directional multiresolution image representation, and it can retain the same dimension of the images of different levels which are obtained by the NSCT, so it can get more information in different levels by appending method. The thesis proposes a new method of image fusion based on NSCT. Firstly, the algorithm uses NSCT to represent the input images at different scales. Then it employs different fusion rules to deal with different images information. The approximation images are processed by averaging the approximation of the input image and the high-frequency detail images in different levels are processed by different fusion rules. The low yield high-frequency detail information is fused by using the grads as activity measure, the improved correlation as match measure and the high yield high-frequency detail information is fused by obtaining the maximum of the MS image and Pan image decompounded by NSCT on the same level. After that, we obtain the composite image by using the inverse transform. Finally, the paper compares the result of method presented in this thesis with others. Although the algorithm increases the computation, the experimental results indicate that images have good qualities.