A New Algorithm of Noised Remote Sensing Image Fusion Based on Steerable Filters

A fusion algorithm of noised remote sensing images based on steerable filters is presented in this paper. A quadrature pair that consists of a steerable filter and its Hilbert transform is used for analyzing the dominant orientation and the local energy in images. By using this algorithm, the original remote sensing images can be denoised, and then their features can be fused successfully. The simulation results indicate that this new remote sensing image fusion algorithm performs well in denoising, preserving, and enhancing edge or texture information. Therefore its comprehensive visual effect is very good.