Using the Second Generation Curvelet to Improve HIS Transform Merge Remote Sensing Images
基于2代Curvelet改进IHS变换的遥感图像融合

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.