Gram-Schmidt Remote Sensing Image Fusion Algorithm Based on Matrix Elementary Transformation

In the application of the Internet of vehicles, it is difficult for a single remote sensing image to have accurate spatial information and spectral information at the same time, so engineers must use image fusion to improve the utilization of remote sensing image information. Aiming at the shortcomings of low spectral resolution and relatively complex programming of traditional fusion algorithms, this paper proposes a Gram-Schmidt remote sensing image fusion algorithm based on matrix elementary transformation, which aims to improve the spatial resolution of multispectral images by using panchromatic images with high spatial resolution. The orthogonalization process of the algorithm in this paper uses the elementary matrix transformation, which is simple and easy to perform. The experimental results show that it can effectively improve the spatial resolution of the original image and has good spectral retention.