A Wavelet Package-Based Data Fusion Method for Multitemporal Remote Sensing Image Processing

Data fusion technique is a powerful tool for extracting higher quality information from large amount remote sensing images and eliminating redundancy among these images. There are many image fusion methods so far, such as IHS, PCA, WT, GLP, etc. Among these methods WT and GLP methods can preserve more images’ spectral characters than others. Traditional multiresolution analysis image fusion methods always decompose multisource or multitemporal images into low and high frequency parts, then fuse the low frequency part of each image into one low frequency part, however, do not deal with fusion to the high frequency parts which represent images’ details, such as edges, corners, ridges, etc. This paper describes a novel wavelet package-based method to fuse multitemporal images, which uses a wavelet package to further decompose multitemporal images at either low or high frequency parts. Then, at the same level, utilizes a threshold and weight algorithm to fuse the corresponding low frequency parts, at the same time applies Lis high-pass filter on fusing the high frequency parts. After that, the fused image will be restored by IDWT, and the fused image will consist of more detailed information and possess better quality. At last, experiment is performed on two multitemporal images to validate this method. Keyword data fusion, multiresolution analysis, wavelet transformation, wavelet package