Remote Sensing Image Fusion Using Edge Information

Abstract

Curvelet Transform, as a method of Multiscale Geometric Analysis(MGA), is more suitable for image processing than wavelet and more appropriate for analyzing the image edge characteristics of curve and line, and it has better approximation precision and sparsity description. In addition, the representation contains more directional information, and contains more directional information. In this paper, The methods of integrating SAR(synthetic aperture radar) image and MS(multi-spectral) image are proposed based on curvelet transform. SAR image and I image, which is given by a linear HSI transform are given by curvelet transform to obtain coarse coefficients and detail coefficients. The new coarse coefficients are obtained by using edge information. The detail coefficients are max of coefficients in original SAR images and I image. Then, the inverse curvelet transform get the new intensity I image (Inew). Finally use Degree of Distortion (DoD) and Space Frequency (SF). etc to evaluate the result. The results of experiment indicate that the method excels those of based on HSI or curvelet transform in preserving spectral information and enhancing resolution.