Study on Data Fusion Methods with Optimal Information Preservation between Spectral and Spatial Based on High Resolution Imagery

Data fusion methods are often employed to balance contradiction between spectral information and spatial information of remotely sensed images. The fused images formed by an effective data fusion method based on remotely sensed data should have both high spectral information preservation with Low Spatial Resolution (LSR) images and high spatial information preservation with High Spatial Resolution (HSR) image. In this paper, Modification Brovey Transform (MBT) has been proposed so as to fuse either individual band LSR images of high resolution imageries. Three fusion methods, such as Smoothing Filter-based Intensity Modulation (SFIM), Discrete Wavelet Transform (DWT) and MBT have been used to fuse Quickbird images and IKONOS images. Both spectral information preservation and spatial information preservation of the fused images generated by three fusion methods based on two kinds of high resolution imageries have been evaluated by qualitative visual interpretation and quantitative statistical analysis. The evaluation results confirm that the proposed method has optimal spatial information preservation with HSR image in both fusion results. Meanwhile, SFIM fusion method has optimal spectral information preservation with LSR images. * Corresponding author. Wenbo Li, [email protected]