Remote sensing image fusion for different spectral and spatial resolutions with bilinear resampling wavelet transform

Abstract

It is an important way that some remote sensing images of different spatial and spectral resolutions are fused to satisfy the requirement of general application. In order to achieve a good fusion result, low spatial spectral images should be sampled. At present, nearest neighbor resampling is often adopted which has some effects on the precision of new image. In this paper, an image fusion method is proposed with bilinear resampling wavelet (BRW) transform, and compared with nearest neighbor resampling wavelet transform. IHS transform and Brovery transform. On the platform of ENVI/IDL, simulations show that the BRW method has good performance for preserving the spectral and spatial resolutions for remote sensing images, with lowest loss of spectral information.