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Content Provider | IET Digital Library |
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Author | Song, Lingfei Fu, Ying Huang, Hua Chen, Yufeng |
Abstract | Hyperspectral imaging has great achievements in agriculture, astronomy, surveillance, and so on. However, the inherent low spatial resolution of hyperspectral imaging, unfortunately, limits its more widespread applications. Recently, hyperspectral image (HSI) super resolution addresses this problem by fusing a low spatial resolution HSI (LR-HSI) with a high spatial resolution multispectral image (HR-MSI), but most of these methods did not consider real-time restoration of high spatial resolution HSI. In this study, the authors propose a fast HSI super-resolution method which fills this blank. Specifically, they model the hyperspectral super resolution as a linear regression problem according to the fact that the imaging process is a linear transform and the inverse of this transform can be approximately estimated, as the spectra of a typical scene lie in a very low-dimensional space. To further exploit the low-dimensional nature of the spectra, they divide the HR-MSI and LR-HSI into several patches and learn the inverse transform patch-by-patch. Experiments on several public datasets show that their method approximates state-of-the-art methods in accuracy, but is several orders of magnitude faster than all of them. Furthermore, they provide an efficient C language implementation of their methods, which can meet the real-time request. |
Starting Page | 1671 |
Ending Page | 1679 |
Page Count | 9 |
ISSN | 17519659 |
Volume Number | 13 |
e-ISSN | 17519667 |
Issue Number | Issue 10, Aug (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/13/10 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5475 |
Journal | IET Image Processing |
Publisher Date | 2019-05-09 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Approximation Theory C Language Implementation Computer Vision And Image Processing Technique Data And Information; Acquisition, Processing, Storage And Dissemination in Geophysics Fast HSI Super Resolution Fast HSI Super-resolution Method Geophysical Image Processing Geophysical Technique And Equipment Geophysics Computing High Spatial Resolution HSI High Spatial Resolution Multispectral Image HR-MSI Hyperspectral Image Hyperspectral Image Super Resolution Hyperspectral Super Resolution Image Fusion Image Reconstruction Image Resolution Imaging Process Inherent Low Spatial Resolution Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Interpolation And Function Approximation Linear Regression Problem Low Spatial Resolution HSI Low-dimensional Space LR-HSI Numerical Analysis Numerical Approximation And Analysis Optical, Image And Video Signal Processing Probability Theory Regression Analysis Remote Sensing Statistics Stochastic Linearised SCUC |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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