Tatsumi Uezato

According to our database, Tatsumi Uezato authored at least 17 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Interpretable Deep Attention Prior for Image Restoration and Enhancement.

Wei He, Tatsumi Uezato, Naoto Yokoya

IEEE Trans. Computational Imaging, 2023

2022

Spectrum-Aware and Transferable Architecture Search for Hyperspectral Image Restoration.

Wei He, Quanming Yao, Naoto Yokoya, Tatsumi Uezato, Hongyan Zhang, Liangpei Zhang

Proceedings of the Computer Vision - ECCV 2022, 2022

Learning Mutual Modulation for Self-supervised Cross-Modal Super-Resolution.

Xiaoyu Dong, Naoto Yokoya, Longguang Wang, Tatsumi Uezato

Proceedings of the Computer Vision - ECCV 2022, 2022

2020

Illumination Invariant Hyperspectral Image Unmixing Based on a Digital Surface Model.

Tatsumi Uezato, Naoto Yokoya, Wei He

IEEE Trans. Image Process., 2020

Hierarchical Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing with Spectral Variability.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

Remote. Sens., 2020

Guided Deep Decoder: Unsupervised Image Pair Fusion.

Tatsumi Uezato, Danfeng Hong, Naoto Yokoya, Wei He

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Hyperspectral Unmixing With Spectral Variability Using Adaptive Bundles and Double Sparsity.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

IEEE Trans. Geosci. Remote. Sens., 2019

LiDAR-Guided Reduction Of Spectral Variability in Hyperspectral Imagery.

Sevcan Kahraman, Raphael Bacher, Tatsumi Uezato, Jocelyn Chanussot, Ali Tangel

Proceedings of the 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2019

2018

Data Set: Hyperspectral image unmixing with LiDAR data-aided spatial regularization.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

Dataset, December, 2018

Hyperspectral Image Unmixing With LiDAR Data-Aided Spatial Regularization.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

IEEE Trans. Geosci. Remote. Sens., 2018

A multiple endmember mixing model to handle spectral variability in hyperspectral unmixing.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

Proceedings of the 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2018

Lidar-Driven Spatial Regularization for Hyperspectral Unmixing.

Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon

Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2016

Incorporating Spatial Information and Endmember Variability Into Unmixing Analyses to Improve Abundance Estimates.

Tatsumi Uezato, Richard J. Murphy, Arman Melkumyan, Anna Chlingaryan

IEEE Trans. Image Process., 2016

A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes.

Tatsumi Uezato, Richard J. Murphy, Arman Melkumyan, Anna Chlingaryan

IEEE Trans. Geosci. Remote. Sens., 2016

A Novel Spectral Unmixing Method Incorporating Spectral Variability Within Endmember Classes.

Tatsumi Uezato, Richard J. Murphy, Arman Melkumyan, Anna Chlingaryan

IEEE Trans. Geosci. Remote. Sens., 2016

2015

Spectral curve-based endmember extraction method.

Tatsumi Uezato, Richard J. Murphy, Arman Melkumyan, Anna Chlingaryan

Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2015

2014

Multiple endmember spectral unmixing within a multi-task framework.

Tatsumi Uezato, Richard J. Murphy, Arman Melkumyan, Anna Chlingaryan, Sven Schneider

Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014