LRTCFPan: Low-Rank Tensor Completion Based Framework for Pansharpening

Author:

Wu Zhong-Cheng1ORCID,Huang Ting-Zhu1ORCID,Deng Liang-Jian1ORCID,Huang Jie1ORCID,Chanussot Jocelyn2ORCID,Vivone Gemine3ORCID

Affiliation:

1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China

2. LJK, CNRS, Inria, Grenoble INP, Université Grenoble Alpes, Grenoble, France

3. Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito Scalo, Italy

Funder

NSFC

Key Projects of Applied Basic Research in Sichuan Province

Natural Science Foundation of Sichuan Province

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 34 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Combining adaptive intensity component extraction and spatial detail injection optimisation for pansharpening;International Journal of Image and Data Fusion;2024-08-27

2. A novel pansharpening model based on two parallel network architectures;International Journal of Remote Sensing;2024-08-09

3. A Novel Fidelity Based on the Adaptive Domain for Pansharpening;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

4. Bayesian tensor network structure search and its application to tensor completion;Neural Networks;2024-07

5. Unsupervised hyperspectral pansharpening via low-rank diffusion model;Information Fusion;2024-07

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