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Blind image fusion for hyperspectral imaging with the directional total variation

Leon Bungert, David A Coomes, Matthias J Ehrhardt, Jennifer Rasch, Rafael Reisenhofer, Carola-Bibiane Schönlieb
2018 Inverse Problems  
This is accomplished by solving a variational problem in which the regularization functional is the directional total variation.  ...  In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality  ...  Furthermore, the authors would like to thank Deimos Imaging for acquiring and providing the data used in this study, and the IEEE GRSS Image Analysis and Data Fusion Technical Committee. M.J.E. and C.  ... 
doi:10.1088/1361-6420/aaaf63 fatcat:j6eppxfstngpvowfrjm6zcogcy

Blind image fusion for hyperspectral imaging with the directional total variation

L Bungert, David Coomes, Matthias Ehrhardt, J Rasch, R Reisenhofer, CB Schönlieb, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository
2018
This is accomplished by solving a variational problem in which the regularization functional is the directional total variation.  ...  In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality  ...  Furthermore, the authors would like to thank Deimos Imaging for acquiring and providing the data used in this study, and the IEEE GRSS Image Analysis and Data Fusion Technical Committee.  ... 
doi:10.17863/cam.25386 fatcat:bmiyiq47efhaxjodijex7arfye

Curvelet based hyperspectral image fusion

Sha Wang, Hua-jun Feng, Zhi-hai Xu, Qi Li, Yue-ting Chen, Lifu Zhang, Jianfeng Yang
2013 International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications  
Hyperspectral image fusion (HIF) reconstructs high spatial resolution hyperspectral images from low spatial resolution hyperspectral images and high spatial resolution multispectral images.  ...  We propose a method for blind HIF problem based on deep learning, where the estimation of the observation model and fusion process are optimized iteratively and alternatingly during the super-resolution  ...  Conclusion In this work, we proposed an iterative fusion framework for blind hyperspectral image fusion.  ... 
doi:10.1117/12.2031476 fatcat:ys2iofucm5dfdoss5njwiv3y44

HYPERSPECTRAL IMAGE RESOLUTION ENHANCEMENT BASED ON SPECTRAL UNMIXING AND INFORMATION FUSION

J. Bieniarz, D. Cerra, J. Avbelj, P. Reinartz, R. Müller
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In order to restore the spatial information of hyperspectral images we propose a hyperspectral and multispectral image fusion method based on spectral unmixing.  ...  The algorithm is tested with HyMAP image data consisting of 125 spectral bands and a simulated multispectral image consisting of 8 bands.  ...  2010) , total variation minimization (Guo et al., 2009) , or Hopfield neural network optimization (Nguyen et al., 2006) .  ... 
doi:10.5194/isprsarchives-xxxviii-4-w19-33-2011 fatcat:fyftnnvc4japdeff4djqttmsou

Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization [article]

Chandrajit Bajaj, Tianming Wang
2019 arXiv   pre-print
Fusing a low-resolution hyperspectral image (HSI) and a high-resolution multispectral image (MSI) of the same scene leads to a super-resolution image (SRI), which is information rich spatially and spectrally  ...  Experiments on various datasets demonstrate the advantages of the proposed algorithm in the quality of fusion and its capability in dealing with unknown spatial degradation.  ...  The rationale is that the directional total variation carries location and direction information of the edges, which are similar for all the bands within the same spectral range.  ... 
arXiv:1902.08224v1 fatcat:csmycrol5bg3pnvft4tgov6dyq

A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization

Miguel Simoes, Jose Bioucas-Dias, Luis B. Almeida, Jocelyn Chanussot
2015 IEEE Transactions on Geoscience and Remote Sensing  
The regularizer, a form of vector Total Variation, promotes piecewise-smooth solutions with discontinuities aligned across the hyperspectral bands.  ...  Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low spatial resolution.  ...  Yifan Zhang for providing the source code for [15] and Dr. Gemine Vivone for providing the source code for the different pansharpening algorithms (GS, GSA, FIHS, PCA, BT an HPF) [57] .  ... 
doi:10.1109/tgrs.2014.2375320 fatcat:mvgtmty43rbrjfrxg7nhjvz7qy

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 9204-9219 Phase Asymmetry Ultrasound Despeckling With Fractional Anisotropic Dif- fusion and Total Variation.  ...  ., +, TIP 2020 5324-5335 Phase Asymmetry Ultrasound Despeckling With Fractional Anisotropic Dif- fusion and Total Variation.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

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

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang,  ...  Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y.,  ...  ., +, TGRS July 2019 4427-4444 Total Variation Regularized Collaborative Representation Clustering With a Locally Adaptive Dictionary for Hyperspectral Imagery.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

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  
Dunbin Shen received the B.His research interests include deep learning and hyperspectral image fusion.  ...  In order to get better performance, we have customized a loss function specifically for the fusion task as well.  ...  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

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  
Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information, which make a plethora of applications for the  ...  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

The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials

Pedram Ghamisi, Kasra Rafiezadeh Shahi, Puhong Duan, Behnood Rasti, Sandra Lorenz, Rene Booysen, Samuel Thiele, Isabel Cecilia Contreras Acosta, Moritz Kirsch, Richard Gloaguen
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
In this review, we assess the relevant recent developments of Machine Learning for the processing of imaging sensor data.  ...  We focus on the description of innovative processing workflows and illustrate the most prominent approaches with examples.  ...  Total variation (TV) denoising [47] is another efficient denoising approach which minimizes the signal variations usingX = arg min X 1 2 H − X 2 F + λT V (X), (4) where T V is the total variation function  ... 
doi:10.1109/jstars.2021.3108049 fatcat:dopyzl427rhmbi7nejpug7ahfq

Table of contents

2020 IEEE Transactions on Image Processing  
Li 9520 A Signal Adaptive Prediction Filter for Video Coding Using Directional Total Variation: Mathematical Framework and Parameter Selection .... J. Rasch, V. Warno, J. Pfaff, C. Tischendorf, D.  ...  Sun 4709 Compressive Radar Imaging of Stationary Indoor Targets With Low-Rank Plus Jointly Sparse and Total Variation Regularizations ........................................................... V.  ... 
doi:10.1109/tip.2019.2940373 fatcat:i7hktzn4wrfz5dhq7hj75u6esa

ADVANCES IN HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION AND SPECTRAL UNMIXING

C. Lanaras, E. Baltsavias, K. Schindler
2015 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The results of our joint fusion and unmixing has the potential to enable more accurate and detailed semantic interpretation of objects and their properties in hyperspectral and multispectral images, with  ...  (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image.  ...  Hueni for useful discussions.  ... 
doi:10.5194/isprsarchives-xl-3-w3-451-2015 fatcat:bfxizlbozbbmnjqjqw4arhomfq

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  ...  In this paper, we propose a variational fusion model with a nonlocal regularization term that encodes patch-based filtering conditioned to the geometry of the multispectral data.  ...  [32] proposed a variational model for simultaneous image fusion and blind deblurring of HS images based on the directional total variation. Mifdal et al.  ... 
doi:10.3390/math9111265 fatcat:ir2ikzradrbsdhx3xpga3px5jq

Remote Sensing Performance Enhancement in Hyperspectral Images

Chiman Kwan
2018 Sensors  
We present a brief review of recent image resolution enhancement algorithms, including single super-resolution and multi-image fusion algorithms, for hyperspectral images.  ...  Hyperspectral images with hundreds of spectral bands have been proven to yield high performance in material classification.  ...  Acknowledgments: Valuable comments and suggestions from the reviewers are deeply appreciated. Conflicts of Interest: The author declares no conflict of interest.  ... 
doi:10.3390/s18113598 fatcat:dheo2a7h5bdbxegryilvixft7a
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