@inproceedings{751a757ea5e04997af0c417a7860caa4,
title = "Dual-Path Optimization Network Based On Spectral Unmixing for Hyperspectral and Multispectral Image Fusion",
abstract = "In this paper, a dual-path optimized fusion network based on spectral unmixing (DPOSU) is proposed for the fusion of hyperspectral image (HSI) and multispectral image (MSI). Based on the spectral mixing model of HSI, an endmember optimization model and an abundance optimization model are constructed respectively. Combining with the observation model, a fusion model for HSI and MSI is then derived. To address the unknown spectral and spatial degradation matrices in the optimization models, a dual-path optimization network is constructed to iteratively update endmember and abundance. Comprehensive experimental results illustrate that the proposed DPOSU network outperforms several typical traditional fusion methods as well as some representative deep learning based fusion methods both visually and quantitatively.",
keywords = "Hyperspectral image, deep network, model contrained, multispectral image, spectral unmixing",
author = "Yifan Zhang and Jiaxin Wang and Bobo Xie and Shaohui Mei",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 ; Conference date: 07-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.1109/IGARSS53475.2024.10642452",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS) ",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9252--9255",
booktitle = "IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
}