Remote sensing image fusion using combining IHS and Curvelet transform

The information content of a single image is mainly limited by the spatial and spectral resolution of the imaging system. Current imaging systems offer a trade-off between high spatial and high spectral resolutions. No single system offers both of these characteristics. In order to obtain the both characteristics in a single image, that is high spatial and spectral resolutions, image fusion technique can be employed. Image fusion is a process of combining two or more images into an image. It can extract features from source images, and provide more information than one image can. In this research, we propose a novel method for multimodality remote sensing image fusion. As a possible remedy for this problem we propose a technique for the fusion of Panchromatic and Multispectral images based on Curvelet transform. This paper introduces new application of the curvelet in multispectral remote sensing image fusion. The methodological approaches proposed in this paper result in merged images with improved quality with respect to those obtained by IHS, DWT, wavelet à trous algorithm and ridgelet and curvelet transform. Results show proposed method preserves more spectral features with less spatial distortion.