An Encoder–Decoder with a Residual Network for Fusing Hyperspectral and Panchromatic Remote Sensing Images

For many urban studies it is necessary to obtain remote sensing images with high hyperspectral and spatial resolution by fusing the panchromatic images. In this article, we propose a deep learning model of an encoder–decoder residual network (EDRN) for image fusion. First, combined circumvent independence features. Second, established extracting representative encoded decoded Finally, networks between encoder decoder enhance extracted We evaluated proposed method on six groups real-world datasets, experimental results confirmed superior performance versus other methods.