A Novel Image Fusion Method Using Curvelet Transform Based on Linear Dependency Test

Because of the benefits of image fusion, although higher resolution remote sensing data are available now, image fusion is still a popular method for better interpreting image data. This paper focuses on a novel region-based image fusion method which facilitates increased flexibility with the definition of a variety of fusion rules. To do that, we use the curvelet transform to merge the details of images. Also, we introduce a fusion rule decision based on the linear algebra that helps to do a better fusion of detail coefficients of the curvelet transform. The experimental results show improvement of the proposed method compared with the well-known methods.