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Spectral Representation vis Data-Guided Sparsity for Hyperspectral Image Super-Resolution†

Xian-Hua Han, YongQing Sun, Jian Wang, Boxin Shi, YinQiang Zheng, Yen-Wei Chen
2019 Sensors  
We propose a novel hyperspectral image superresolution method via non-negative sparse representation of reflectance spectra with a data guided sparsity constraint.  ...  for recovering the target high resolution hyperspectral image.  ...  This study proposes a data guided sparsity regularized nonnegative spectral representation for the hyperspectral superresolution task.  ... 
doi:10.3390/s19245401 fatcat:uwbtp5ycyfb3joqg642xii6eea

High-resolution hyperspectral imaging via matrix factorization

Rei Kawakami, Yasuyuki Matsushita, John Wright, Moshe Ben-Ezra, Yu-Wing Tai, Katsushi Ikeuchi
2011 CVPR 2011  
In this paper, we introduce a simple new technique for reconstructing a very high-resolution hyperspectral image from two readily obtained measurements: A lower-resolution hyperspectral image and a high-resolution  ...  Hyperspectral imaging is a promising tool for applications in geosensing, cultural heritage and beyond.  ...  Once the basis A is recovered, we reconstruct Z using sparsity as a guide.  ... 
doi:10.1109/cvpr.2011.5995457 dblp:conf/cvpr/KawakamiMWBTI11 fatcat:s3pckt42xzcgzcbfcjgmepeca4

Table of contents

2020 IEEE Transactions on Geoscience and Remote Sensing  
Bi 6197 Hyperspectral Data Subpixel-Pixel-Superpixel Guided Fusion for Hyperspectral Anomaly Detection ....... Z. Huang, L. Fang, and S.  ...  Sparse Super-Resolution Method for Radar Forward-Looking Imaging .................................................. ...............................................  ... 
doi:10.1109/tgrs.2020.3006605 fatcat:g45mqghjmjenlfd2ydw7nzbcju

Hyperspectral Image Super-Resolution With Optimized RGB Guidance

Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
To overcome the limitations of existing hyperspectral cameras on spatial/temporal resolution, fusing a low resolution hyperspectral image (HSI) with a high resolution RGB (or multispectral) image into  ...  Previous methods for this fusion task usually employ hand-crafted priors to model the underlying structure of the latent high resolution HSI, and the effect of the camera spectral response (CSR) of the  ...  the task of RGB-guided HSI super-resolution.  ... 
doi:10.1109/cvpr.2019.01193 dblp:conf/cvpr/FuZZZ019 fatcat:zbmb5ssbuvcnta355zh45n5rwu

Hyperspectral Image Super-Resolution Using Optimization and DCNN-Based Methods [chapter]

Xian-Hua Han
2019 Processing and Analysis of Hyperspectral Data [Working Title]  
prior knowledge such as representation sparsity, spectral physical properties, spatial smoothness, and so on.  ...  The optimization-based approaches estimate HR-HS image via minimizing the reconstruction errors of the available low-resolution hyperspectral and high-resolution multispectral images with different constrained  ...  Processing and Analysis of Hyperspectral Data Hyperspectral Image Super-Resolution Using Optimization and DCNN-Based Methods DOI: http://dx.doi.org/10.5772/intechopen.89243 Hyperspectral Image  ... 
doi:10.5772/intechopen.89243 fatcat:rxalxrj3yre2zccqwfpqbxqn4a

2020 Index IEEE Transactions on Computational Imaging Vol. 6

2020 IEEE Transactions on Computational Imaging  
., +, TCI 2020 1362-1374 Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imag- ery.  ...  ., +, TCI 2020 1362-1374 Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery.  ...  ., +, TCI 2020 125-137 Truncation Correction for X-ray Phase-Contrast Region-of-Interest Tomography. Felsner, L., +, TCI 2020 625-639  ... 
doi:10.1109/tci.2021.3054596 fatcat:puij7ztll5ai7alxrmqzsupcny

Hyperspectral Super-Resolution with Spectral Unmixing Constraints

Charis Lanaras, Emmanuel Baltsavias, Konrad Schindler
2017 Remote Sensing  
That information is required for the super-resolution, but often at most approximately known for real-world images.  ...  The process of fusing the two types of imagery into a product with both high spatial and spectral resolution is called hyperspectral super-resolution.  ...  images".  ... 
doi:10.3390/rs9111196 fatcat:wbjxz3oxczhaxihvpj5o5a62qm

Table of contents

2021 IEEE Transactions on Geoscience and Remote Sensing  
436 Hyperspectral 436 Data Residual Spectral-Spatial Attention Network for Hyperspectral Image Classification ...................................... ....................................................  ...  Zhang 629 Hyperspectral and Multispectral Image Fusion via Graph Laplacian-Guided Coupled Tensor Decomposition ......... ......................................... Y. Bu, Y. Zhao, J. Xue, J. C.-W.  ... 
doi:10.1109/tgrs.2020.3039449 fatcat:sxee5msl55emhnszejgpf6vrpa

Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration [article]

Yi Chang, Luxin Yan, Houzhang Fang, Sheng Zhong, Zhijun Zhang
2017 arXiv   pre-print
), and down-sampled (both spectral and spatial downsample, HSI super-resolution).  ...  Hyperspectral imaging, providing abundant spatial and spectral information simultaneously, has attracted a lot of interest in recent years.  ...  HSI Super-resolution HSI super-resolution refers to the fusion of a hyperspectral image (low spatial but high spectral resolution) with a panchromatic/multispectral image (high spatial but low spectral  ... 
arXiv:1709.00192v1 fatcat:ueremc3lzvhlna42pgngpgb3ka

Hyperspectral Image Super-Resolution via Deep Prior Regularization with Parameter Estimation [article]

Xiuheng Wang, Jie Chen, Qi Wei, Cédric Richard
2021 arXiv   pre-print
Hyperspectral image (HSI) super-resolution is commonly used to overcome the hardware limitations of existing hyperspectral imaging systems on spatial resolution.  ...  It fuses a low-resolution (LR) HSI and a high-resolution (HR) conventional image of the same scene to obtain an HR HSI.  ...  Here, we aim at performing hyperspectral super-resolution by combining the physical model-based optimization and deep learning for constructing data-driven priors.  ... 
arXiv:2009.04237v2 fatcat:cnfpwuoi3zfg3nbgxktqh3lieu

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Model-Guided Deep Hyperspectral Image Super-Resolution. Dong, W., +, Progressive Diversified Augmentation for General Robustness of DNNs: A spectral Image Super-Resolution.  ...  ., Hyperspectral Image Super-Resolution via Deep Progressive Zero-Centric H LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image Deep Learning-Based Forgery Attack on Document Images.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 4568-4582 Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability.  ...  ., +, TIP 2020 4568-4582 Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Table of Contents [EDICS]

2021 IEEE Transactions on Computational Imaging  
Ye Hyperspectral Imagery Spatial Super-Resolution Using Generative Adversarial Network . . . . . . . . . . . . . . . . . . . . . . . . . . . ..Deep Equilibrium Architectures for Inverse Problems in Imaging  ...  Kamilov SRNSSI: A Deep Light-Weight Network for Single Image Super Resolution Using Spatial and Spectral Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tci.2022.3143315 fatcat:ul2dbyjijvh7ha44zeuftxanfi

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

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Refo-cusing and Zoom-In Polar Format Algorithm for 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.,  ...  ., +, TGRS July 2019 5043-5053 Spectral Super Resolution of Hyperspectral Images via Coupled Dictionary Learning.  ...  ., +, TGRS Aug. 2019 6169-6181 Spectral Super Resolution of Hyperspectral Images via Coupled Dictionary Learning.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Table of contents

2020 IEEE Transactions on Image Processing  
Fu 100 Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability ... .............................................................. R.  ...  Ding 7317 A Truncated Matrix Decomposition for Hyperspectral Image Super-Resolution ............................................ ........................................................................  ... 
doi:10.1109/tip.2019.2940373 fatcat:i7hktzn4wrfz5dhq7hj75u6esa
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