Remote Sensing Satellite Image Fusion Using Fast Curvelet Transforms

This paper presents a novel fusion rule via high pass modulation using Local Magnitude Ratio (LMR) in Fast Discrete Curvelet Transforms (FDCT) domain. It is based on the Fourier and wavelet transform methods, which retain rich multispectral details but less spatial details from source images. Wavelets perform well only at linear features but not at non linear discontinuities because they do not use the geometric properties of structures. Curvelet transforms overcome such difficulties in feature representation. In this method Indian Remote Sensing (IRS) Resourcesat-1 LISS IV satellite sensor image of spatial resolution of 5.8m is used as low resolution (LR) multispectral image and Cartosat-1 Panchromatic (Pan) of spatial resolution 2.5m is used as high resolution (HR) Pan image. This fusion rule generates HR multispectral image at 2.5m spatial resolution. The method has been compared with values obtained from different techniques such as Wavelet, Principal component analysis (PCA), High pass filtering (HPF), Modified Intensity-Hue-Saturation (M. IHS) and Grams-Schmidth fusion methods. Some experimental results and conclusions about the performance of the method are presented.