Satellite Image Fusion Based on Improved Fast Discrete Curvelet Transforms

Abstract

Image fusion is the process of merging two or more images into a more informative single image. Satellite image fusion uses high resolution panchromatic image and low resolution multispectral image. IHS, Brovery, PCA, Wavelet, Curvelet etc are the existing techniques available for image fusion. But simultaneous retention of spatial and spectral resolution is an important concern in remote sensing applications. In this paper we proposed an improved Satellite image fusion method based on Fast Discrete curvelet Transform (FDCT) via wrapping. The method uses an improved fusion rule, were the maximum FDCT coefficients from each cell of the Intensity component of the MS image and histogram matched PAN image are taken. The resulting image is then undergone a comparative analysis with the outcomes of existing methodologies. The comparative analysis proves that the proposed method retains more spatial and spectral details than other methods.