Abstract
Due to the physical hardware limits, multi-spectral (MS) images often suffer from low-spatial resolution, challenging their practical utility in real applications. Therefore, pan-sharpening technology has been widely explored as a popular tool to generate images with both high-spatial and high-spectral resolutions by integrating PAN and MS images. In this paper, we propose an effective pan-sharpening network, which consists of two core designs: a PAN-guided band-aware multi-spectral feature enhancement module and a multi-focus feature fusion module. To be specific, the former exploits the PAN features to perform band-aware multi-spectral feature modulation and selectively enhance the information of each spectral band while the latter covers various convolution kernels to extract multi-scale features, benefiting the fusion performance of the remote sensing scene. Equipped with the above core modules, our proposed framework is capable of achieving the best performance when compared with existing state-of-the-art Pan-sharpening methods over multiple satellite datasets. Extensive ablation studies are additionally conducted to verify the effectiveness of our key components both visually and quantitatively. The source code is released at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/manman1995/Awaresome-pansharpening</uri> .
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.