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Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution [article]

Oleksii Sidorov, Jon Yngve Hardeberg
2019 arXiv   pre-print
In this work, we propose a new approach to denoising, inpainting, and super-resolution of hyperspectral image data using intrinsic properties of a CNN without any training.  ...  However, the latter becomes an issue for hyperspectral image processing where datasets commonly consist of just a few images.  ...  The majority of hyperspectral super-resolution (SR) algorithms perform a fusion of input hyperspectral image with a high-resolution multispectral image which is easier to obtain [11] [25] .  ... 
arXiv:1902.00301v2 fatcat:bbxosl6tdzcnjexxgfa22demvy

Regularizing Subspace Representation for Fusing Hyperspectral and Multispectral Images

Yanhong Yang, Congcong Wang, Yuan Feng, Zhang Jianhua, Yuhui Zheng, Sheng Yong Chen
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Fusing a low spatial resolution hyperspectral image (LR-HSI) with a high spatial but low spectral resolution multispectral image (HR-MSI) has been regarded as an effective approach to obtain high resolution  ...  Therefore, to effectively fuse the LR-HSI and HR-MSI information, and meanwhile avoid the impact of mixed noise, in this paper, we introduce a denoising regularized subspace representation based HSI-MSI  ...  Similarly, in [18] , a CNN denoiser was used to regularize the HSI-MSI fusion. However, most of the fusion methods only take Gaussian noise into consideration [18, 19] .  ... 
doi:10.1109/jstars.2021.3130719 fatcat:giovzundn5bzthdtilygp2vjgy

Table of contents

2021 IEEE Transactions on Geoscience and Remote Sensing  
Chanussot 2269 Hyperspectral Data Hyperspectral Image Classification With Attention-Aided CNNs .............................................................. ...........................................  ...  Long 2155 FEC: A Feature Fusion Framework for SAR Target Recognition Based on Electromagnetic Scattering Features and Deep CNN Features .................................................................  ... 
doi:10.1109/tgrs.2021.3052119 fatcat:obk5h6sp2nh47ounq4jqlhukcu

Variational Fusion of Hyperspectral Data by Non-Local Filtering

Jamila Mifdal, Bartomeu Coll, Jacques Froment, Joan Duran
2021 Mathematics  
Hyperspectral image fusion consists in merging the spectral information of a hyperspectral image with the geometry of a multispectral one in order to infer an image with high spatial and spectral resolutions  ...  and hyperspectral images.  ...  The reference images are denoised with a routine provided by Naoto Yokoya (https:// openremotesensing.net/knowledgebase/hyperspectral-and-multispectral-data-fusion/, accessed on 7 March 2021) [6] before  ... 
doi:10.3390/math9111265 fatcat:ir2ikzradrbsdhx3xpga3px5jq

A Twice Optimizing Net with Matrix Decomposition for Hyperspectral and Multispectral Image Fusion

Dunbin Shen, Jianjun Liu, Zhiyong Xiao, Jinlong Yang, Liang Xiao
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Index Terms-Convolutional neural network (CNN), hyperspectral image, image fusion, loss function, super resolution.  ...  Fusing a low-resolution hyperspectral (LRHS) image and a high-resolution multispectral (HRMS) image to generate a high-resolution hyperspectral (HRHS) image has grown a significant and attractive application  ...  Gamba from the University of Pavia for providing the PU dataset, they would also like to thank the National Center for Airborne Laser Mapping, the Hyperspectral Image Analysis Laboratory, the University  ... 
doi:10.1109/jstars.2020.3009250 fatcat:jtti37m7f5bcfnwna4e2pz4qiu

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
and Hanssen, R.F., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging  ...  Hu, C., Zhang, B., Dong, X., and Li, Y., Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite; TGRS Sept. 2019 6591-6607 Hu, F., Wu, J., Chang, L.,  ...  ., +, TGRS Feb. 2019 866-880 Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 2861-2873 Deep Collaborative Attention Network for Hyperspectral Image Classification by Combining 2-D CNN and 3-D CNN.  ...  ., +, JSTARS 2020 4809-4815 Deep Collaborative Attention Network for Hyperspectral Image Classification by Combining 2-D CNN and 3-D CNN.  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

A Meta-Analysis of Convolutional Neural Networks for Remote Sensing Applications

Masoud Mahdianpari, Hamid Ghanbari, Fariba Mohammadimanesh, Saeid Homayouni
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
and data types, and 2) algorithm specifications, such as different types of CNN models, parameter settings, and reported accuracies.  ...  This article presents a meta-analysis of 416 peer-reviewed journal articles, summarizes CNN advancements, and its current status under RS applications.  ...  [30] was conducted on RS image enhancement, including super-resolution, denoising, restoration, pan-sharpening, and fusion.  ... 
doi:10.1109/jstars.2021.3065569 fatcat:jn4dzywhuvaublx2aoat2tsfga

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 7565-7577 Hyperspectral and Multispectral Image Fusion Using Optimized Twin Dictionaries.  ...  ., +, TIP 2020 7751-7764 Dictionaries Hyperspectral and Multispectral Image Fusion Using Optimized Twin Dic- tionaries.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Table of contents

2020 IEEE Transactions on Geoscience and Remote Sensing  
Plaza 2817 A Single Model CNN for Hyperspectral Image Denoising ..................................................................... .............................................. A. Maffei, J. M.  ...  He 2352 Deep Feature Fusion via Two-Stream Convolutional Neural Network for Hyperspectral Image Classification ......... ................................................................................  ... 
doi:10.1109/tgrs.2020.2973519 fatcat:pus5uerid5ggdhfoxc5lts3p6y

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion [article]

Huanfeng Shen, Menghui Jiang, Jie Li, Chenxia Zhou, Qiangqiang Yuan, Liangpei Zhang
2021 arXiv   pre-print
In the fields of image restoration and image fusion, model-driven methods and data-driven methods are the two representative frameworks.  ...  The typical existing and potential coupling methods for remote sensing image restoration and fusion are introduced with application examples.  ...  This includes panchromatic (PAN)/multispectral image (MSI) fusion, PAN/ HSI fusion, and MSI/HSI fusion. PAN/HSI fusion can be regarded as a special case of MSI/HSI fusion.  ... 
arXiv:2108.06073v1 fatcat:vdnabzwvvnbvnllrlvzvvqgolm

Table of contents

2021 IEEE Transactions on Geoscience and Remote Sensing  
Benediktsson 7680 l 0 -l 1 Hybrid Total Variation Regularization and Its Applications on Hyperspectral Image Mixed Noise Removal and Compressed Sensing .................................................  ...  Li, and R. Gloaguen 7726 A Tensor Subspace Representation-Based Method for Hyperspectral Image Denoising .................................... ... J. Boutin, J.-L. Vergely, E. P. Dinnat, P.  ... 
doi:10.1109/tgrs.2021.3101068 fatcat:mvo372ljtzaxrl2kd2rccrbyai

2019 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 12

2019 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., and Lopez, J.F  ...  ., +, JSTARS Oct. 2019 4131-4148 Fusion of Hyperspectral and Multispectral Images Based on a Bayesian Nonparametric Approach.  ...  ., +, JSTARS July 2019 2107-2120 Fusion of Hyperspectral and Multispectral Images Based on a Bayesian Nonparametric Approach.  ... 
doi:10.1109/jstars.2020.2973794 fatcat:sncrozq3fjg4bgjf4lnkslbz3u

Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition

Marzieh Zare, Mohammad Sadegh Helfroush, Kamran Kazemi, Paul Scheunders
2021 Remote Sensing  
Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing  ...  The proposed method performs a tucker tensor factorization of a low resolution hyperspectral image and a high resolution multispectral image under the constraint of non-negative tensor decomposition (NTD  ...  The authors also highly appreciate the time and consideration of the editors and the anonymous referees for their constructive suggestions that greatly improved the paper.  ... 
doi:10.3390/rs13152930 fatcat:shtzar6w5bcidp4imtaq3ley7y

Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

Pedram Ghamisi, Naoto Yokoya, Jun Li, Wenzhi Liao, Sicong Liu, Javier Plaza, Behnood Rasti, Antonio Plaza
2017 IEEE Geoscience and Remote Sensing Magazine  
reduction, resolution enhancement, hyperspectral image denoising and restoration, change detection, and fast computing.  ...  Hence, rigorous and innovative methodologies are required for hyperspectral image and signal processing and have become a center of attention for researchers worldwide.  ...  and Data Fusion Technical Committee for organizing the 2013 Data Fusion Contest.  ... 
doi:10.1109/mgrs.2017.2762087 fatcat:6ezzye7yyvacbouduqv2f2c7gi
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