MSAN: Multiscale self-attention network for pansharpening
Authors:
- Hangyuan LuHLHangyuan Lu
- Yong YangYYYong Yang
- Shuying HuangSHShuying Huang
- Rixian LiuRLRixian Liu
- Huimin GuoHGHuimin Guo
Top Cited Papers
- 13 February 2025
- journal article
- Published by Elsevier in Pattern Recognition
- Vol. 162
Abstract
No abstract availableFunding Information
- Natural Science Foundation of Tianjin Municipality (24JCZDJC00130)
- National Natural Science Foundation of China (62362035, 62072218)
This publication has 29 references indexed in Scilit:
- Unsupervised hyperspectral pansharpening via low-rank diffusion modelInformation Fusion, 2024
- Intensity mixture and band-adaptive detail fusion for pansharpeningPattern Recognition, 2023
- Cross-modality attentive feature fusion for object detection in multispectral remote sensing imageryPattern Recognition, 2022
- Pan-sharpening based on multi-objective decision for multi-band remote sensing imagesPattern Recognition, 2021
- An efficient and high-quality pansharpening model based on conditional random fieldsInformation Sciences, 2021
- A review of image fusion techniques for pan-sharpening of high-resolution satellite imageryISPRS Journal of Photogrammetry and Remote Sensing, 2021
- Pansharpening Based on Joint-Guided Detail ExtractionIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
- Deep learning in remote sensing applications: A meta-analysis and reviewISPRS Journal of Photogrammetry and Remote Sensing, 2019
- PanNet: A Deep Network Architecture for Pan-Sharpening2017
- A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulationISPRS Journal of Photogrammetry and Remote Sensing, 2014