Curvelet

as a new multi scale analysis algorithm

is more suitable for image processing than wavelet

and is more appropriate for the analysis of the image edges such as curve and line characteristics. In addition

the representation contains more directional information. In this paper the theory and implementation of the second generation Curvelet transform is reviewed. The methods of remote sensing image fusion are proposed based on Curvelet transform and the scheme using Curvelet and IHS transform is described in detail. The processing of fusion is performed with the high resolution panchromatic and low resolution multispectral remote sensing images. The result of experiment indicates that the performance of Curvelet based image fusion method excels those of based IHS or wavelet transform. When the Curvelet transform is introduced to image fusion

original images are characterized better and more information for fusion is obtained.It not only preserves spectral information of the original multispectral image well

but also enhances spatial information with more datails.