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Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach

Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma
2018 IEEE Transactions on Signal Processing  
Hyperspectral super-resolution refers to the problem of fusing a hyperspectral image (HSI) and a multispectral image (MSI) to produce a super-resolution image (SRI) that has fine spatial and spectral resolution  ...  In this work, we propose to tackle the super-resolution problem from a tensor perspective.  ...  Abstract-Hyperspectral super-resolution refers to the problem of fusing a hyperspectral image (HSI) and a multispectral image (MSI) to produce a super-resolution image (SRI) that has fine spatial and spectral  ... 
doi:10.1109/tsp.2018.2876362 fatcat:gzfe24o5mjfzlf2azoxdcik7am

Super-resolution reconstruction of hyperspectral images

T. Akgun, Y. Altunbasak, R.M. Mersereau
2005 IEEE Transactions on Image Processing  
The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene.  ...  In this paper we introduce a novel superresolution reconstruction method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process.  ...  INTRODUCTION One of the most expensive parameters in a space imaging system is the spatial resolution. Unfortunately, it is also one of the hardest to improve.  ... 
doi:10.1109/tip.2005.854479 pmid:16279185 fatcat:vsr4ssaof5hwvaua4tktbm5sny

Super-resolution of hyperspectral images using local spectral unmixing

G. Licciardi, M.A. Veganzones, M. Simoes, J. Bioucas, J. Chanussot
2014 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)  
On this regards, hyperspectral and multispectral images have complementary characteristics in terms of spectral and spatial resolutions.  ...  On a first step the hyperspectral image is spectrally downsampled in order to match the multispectral one.  ...  HYPERSPECTRAL SUPER RESOLUTION In order to better understand the proposed approach,we define X ∈ R m×n as the super-resolution hyperspectral image having m spectral bands and n pixels.  ... 
doi:10.1109/whispers.2014.8077569 dblp:conf/whispers/LicciardiVSBC14 fatcat:vlb6i63spvg5ncja2npjs65xo4

Hyperspectral Image Super-Resolution Based on Tensor Spatial-Spectral Joint Correlation Regularization

Yinghui Xing, Shuyuan Yang, Licheng Jiao
2020 IEEE Access  
Compared with natural image super-resolution, hyperspectral image super-resolution (HSR) is more complex because the redundancy in spectral bands and spatial information.  ...  INDEX TERMS Hyperspectral image, low-rank analysis, spatial-spectral joint correlation, super-resolution, tensor decomposition. 63654 This work is licensed under a Creative Commons Attribution 4.0 License  ...  Hyperspectral image super-resolution (HSR), which is also known as hyperspectral and multispectral image fusion, aims to integrate information from an HSI and a co-registered MSI, to obtain a super-resolution  ... 
doi:10.1109/access.2020.2982494 fatcat:h2yecjcmbbgu5oiqn6kyy5qfm4

Hyperspectral Super-Resolution by Coupled Spectral Unmixing

Charis Lanaras, Emmanuel Baltsavias, Konrad Schindler
2015 2015 IEEE International Conference on Computer Vision (ICCV)  
Hyperspectral super-resolution addresses this problem, by fusing a lowresolution hyperspectral image and a conventional highresolution image into a product of both high spatial and high spectral resolution  ...  In experiments with two benchmark datasets we show that the proposed approach delivers improved hyperspectral super-resolution.  ...  This procedure is referred to as hyperspectral image fusion or hyperspectral super-resolution.  ... 
doi:10.1109/iccv.2015.409 dblp:conf/iccv/LanarasBS15 fatcat:utsbz7pp2bf4bkt32zas5tarsy

Hyperspectral Image Super-Resolution Based on Spatial Group Sparsity Regularization Unmixing

Jun Li, Yuanxi Peng, Tian Jiang, Longlong Zhang, Jian Long
2020 Applied Sciences  
In this paper, we propose a spatial group sparsity regularization unmixing-based method for hyperspectral super-resolution.  ...  Hyperspectral super-resolution aims to fuse a low spatial resolution HSI with a conventional high spatial resolution image, producing an HSI with high resolution in both the spectral and spatial dimensions  ...  HSI super-resolution is a fundamental and essential problem in the field of hyperspectral imaging, based on the simple idea of fusing the spectral information of hyperspectral images with the spatial information  ... 
doi:10.3390/app10165583 fatcat:7xc3ywjurzehdjc6mhwn3qzbbi

Hyperspectral Image Super-Resolution Based on Spatial Correlation-Regularized Unmixing Convolutional Neural Network

Xiaochen Lu, Dezheng Yang, Junping Zhang, Fengde Jia
2021 Remote Sensing  
Experiments on three public remote sensing HS images demonstrate the feasibility and superiority in terms of spectral fidelity, compared with some state-of-the-art HS image super-resolution methods.  ...  Super-resolution (SR) technology has emerged as an effective tool for image analysis and interpretation.  ...  Gamba for providing the ROSIS data over Pavia; to the Hyperspectral Image Analysis group and the NSF Funded Center for Airborne Laser Mapping (NCALM) at the University of Houston; and to the IEEE GRSS  ... 
doi:10.3390/rs13204074 fatcat:hl7uaogyivevzlopjiu6kevp3a

Bayesian sparse representation for hyperspectral image super resolution

Naveed Akhtar, Faisal Shafait, Ajmal Mian
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We propose a hyperspectral image super resolution approach that fuses a high resolution image with the low resolution hyperspectral image using non-parametric Bayesian sparse representation.  ...  The computed codes are used with the estimated scene spectra to construct the super resolution hyperspectral image.  ...  Our objective is to estimate the super resolution hyperspectral image T ∈ R M ×N ×L by fusing Y and Y h .  ... 
doi:10.1109/cvpr.2015.7298986 dblp:conf/cvpr/AkhtarSM15 fatcat:36776a2h6nfibj7vdtl3h2wh5i

Super‑Resolution for Hyperspectral Remote Sensing Images Based on the 3D Attention‑SRGAN Network

Xinyu Dou, Chenyu Li, Qian Shi, Mengxi Liu
2020 Remote Sensing  
In the superresolution (SR) field, many methods have been focusing on the restoration of the spatial information while ignoring the spectral aspect.  ...  Firstly, we innovatively used three-dimensional (3D) convolution based on SRGAN (SuperResolution Generative Adversarial Network) structure to not only exploit the spatial features but also preserve spectral  ...  Figure 3 . 3 The framework of proposed three-dimensional Attention-based Super-Resolution Generative Adversarial Network (3DASRGAN) for SR of hyperspectral remote sensing images (HSIs).  ... 
doi:10.3390/rs12071204 fatcat:r3loz42mkvf7npj7jp65h5ttfy

Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution

Ying Qu, Hairong Qi, Chiman Kwan
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
This paper focuses on hyperspectral image super-resolution (HSI-SR), where a hyperspectral image (HSI) with low spatial resolution (LR) but high spectral resolution is fused with a multispectral image  ...  However, due to hardware limitations, one can only expect to acquire images of high resolution in either the spatial or spectral domains.  ...  This procedure is referred to as hyperspectral image super-resolution (HSI-SR) [3, 27, 8] as shown in Fig. 1 .  ... 
doi:10.1109/cvpr.2018.00266 dblp:conf/cvpr/QuQK18 fatcat:fiyzz2bau5fixkmzgjvkwzdm3y

Coupled Convolutional Neural Network With Adaptive Response Function Learning for Unsupervised Hyperspectral Super Resolution

Ke Zheng, Lianru Gao, Wenzhi Liao, Danfeng Hong, Bing Zhang, Ximin Cui, Jocelyn Chanussot
2020 IEEE Transactions on Geoscience and Remote Sensing  
Hyperspectral super-resolution refers to fusing HSI and MSI to generate an image with both high spatial and high spectral resolutions.  ...  Due to the limitations of hyperspectral imaging systems, hyperspectral imagery (HSI) often suffers from poor spatial resolution, thus hampering many applications of the imagery.  ...  Naoto Yokoya for providing MATLAB codes for hyperspectral and multispectral data fusion toolbox  ... 
doi:10.1109/tgrs.2020.3006534 fatcat:u24k5a5vpncirhbourj5yzb2fu

Hyperspectral Image Super-Resolution via Non-local Sparse Tensor Factorization

Renwei Dian, Leyuan Fang, Shutao Li
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Hyperspectral image (HSI) super-resolution, which fuses a low-resolution (LR) HSI with a high-resolution (HR) multispectral image (MSI), has recently attracted much attention.  ...  In this paper, a novel HSI super-resolution method based on non-local sparse tensor factorization (called as the NLSTF) is proposed.  ...  To the best of our knowledge, no sparse tensor factorization method has been used for the hyperspectral image super-resolution.  ... 
doi:10.1109/cvpr.2017.411 dblp:conf/cvpr/DianFL17 fatcat:mr3araxxrbdrndxvxmua45fvny

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)  
RGB camera on super-resolution accuracy has rarely been investigated.  ...  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  ...  Finally, we implement our HSI super-resolution method on the real images.  ... 
doi:10.1109/cvpr.2019.01193 dblp:conf/cvpr/FuZZZ019 fatcat:zbmb5ssbuvcnta355zh45n5rwu

Hyperspectral imagery super-resolution by sparse representation and spectral regularization

Yongqiang Zhao, Jinxiang Yang, Qingyong Zhang, Lin Song, Yongmei Cheng, Quan Pan
2011 EURASIP Journal on Advances in Signal Processing  
Hyperspectral imagery is intrinsically sparse in spatial and spectral domains, and image super-resolution quality largely depends on whether the prior knowledge is utilized properly.  ...  In this article, we propose a novel hyperspectral imagery super-resolution method by utilizing the sparse representation and spectral mixing model.  ...  Based on these ideas, a novel hyperspectral image super-resolution method is proposed in this article.  ... 
doi:10.1186/1687-6180-2011-87 fatcat:4mykwkaobneznbfkcshecahxfq

Super-resolution land-cover mapping based on the selective endmember spectral mixture model in hyperspectral imagery

Liangpei Zhang
2011 Optical Engineering: The Journal of SPIE  
Then the complete algorithm integrating SESM and super-resolution mapping based on a back-propagation neural network is evaluated.  ...  Due to the reliance on this flawed spectral mixture model, the super-resolution mapping is unable to represent detail in the following result image precisely and effectively.  ...  Test of Complete Super-Resolution Mapping Algorithm The super-resolution mapping algorithm should be applied on fraction images of low spatial resolution.  ... 
doi:10.1117/1.3660527 fatcat:3fwvjwpkxfdg7own3kbnlcel34
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