Remote Sensing Image Fusion Based On IHS and Dual Tree Compactly Supported Shearlet Transform

Abstract

This paper presents a novel remote sensing image fusion algorithm, which implements the intensity-hue-saturation (IHS) transform on panchromatic sharpening of multispectral data and the dual-tree compactly supported shearlet transform (DT CSST) during fusion. Shearlet transforms can provide almost optimal representation of the anisotropic features of an image. The spatial domain discrete implementation, the compactly supported shearlet transform (CSST), which represents the directions by dilation operations, are selected in the proposed fusion method. Since most of the prominent features of images, such as edges and regions, have limited sizes in the spatial domain, CSST is very suitable for image fusion. However, the conventional CSST is shift-variant, which causes distortions in fused images. With the embedded dual-tree (DT) sturcture in the CSST, the shift-variant properties can be effectively reduced. Combining the IHS transform and the DT CSST, an effective panchromatic and multispectral image fusion method is proposed in this paper. The experiments’ results suggest that the proposed method extract more spatial information from panchromatic images with less lost in spectral consistency compared to other fusion methods which are based on discrete wavelet transform (DWT), a trous wavelet transform, a trous shearlet transform, the dual-tree complex wave transform ( DT CWT), or the Curvelet transform.