Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information

Hyperspectral (HS) images usually have high spectral resolution and low spatial resolution (LSR). However, multispectral (MS) images have high spatial resolution (HSR) and low spectral resolution. HS–MS image fusion technology can combine both advantages, which is beneficial for accurate feature cla...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2020-03, Vol.12 (6), p.1009
Main Authors: Feng, Xiaoxiao, He, Luxiao, Cheng, Qimin, Long, Xiaoyi, Yuan, Yuxin
Format: Article
Language:English
Subjects:
Bands
Computer vision
Decomposition
endmember spatial information
hyperspectral image
Image processing
Image retrieval
Methods
Multisensor fusion
multispectral image
Noise
Remote sensing
Spatial data
Spatial resolution
Spectra
Spectral resolution
spectral unmixing
temporal difference
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Summary:Hyperspectral (HS) images usually have high spectral resolution and low spatial resolution (LSR). However, multispectral (MS) images have high spatial resolution (HSR) and low spectral resolution. HS–MS image fusion technology can combine both advantages, which is beneficial for accurate feature classification. Nevertheless, heterogeneous sensors always have temporal differences between LSR-HS and HSR-MS images in the real cases, which means that the classical fusion methods cannot get effective results. For this problem, we present a fusion method via spectral unmixing and image mask. Considering the difference between the two images, we firstly extracted the endmembers and their corresponding positions from the invariant regions of LSR-HS images. Then we can get the endmembers of HSR-MS images based on the theory that HSR-MS images and LSR-HS images are the spectral and spatial degradation from HSR-HS images, respectively. The fusion image is obtained by two result matrices. Series experimental results on simulated and real datasets substantiated the effectiveness of our method both quantitatively and visually.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs12061009