Online Service PortalDo you have any questions or suggestions regarding our devices, products, experiments, equipment sets or about our software? You need spare parts? FORM

LaserOptics Gun

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

LaserOptics for Rifle

Feng, X.; He, L.; Cheng, Q.; Long, X.; Yuan, Y. Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information. Remote Sens. 2020, 12, 1009. https://doi.org/10.3390/rs12061009

Feng X, He L, Cheng Q, Long X, Yuan Y. Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information. Remote Sensing. 2020; 12(6):1009. https://doi.org/10.3390/rs12061009

Feng, Xiaoxiao, Luxiao He, Qimin Cheng, Xiaoyi Long, and Yuxin Yuan. 2020. "Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information" Remote Sensing 12, no. 6: 1009. https://doi.org/10.3390/rs12061009

Laseroptics procedure

JavaScript seems to be disabled in your browser. You must have JavaScript enabled in your browser to utilize the functionality of this website.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Laser opticsurgery

Laseroptics Physics

Abstract: 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. Keywords: hyperspectral image; multispectral image; remote sensing; temporal difference; spectral unmixing; endmember spatial information

Laseroptics course

LaserOptics pdf

Feng, Xiaoxiao, Luxiao He, Qimin Cheng, Xiaoyi Long, and Yuxin Yuan. 2020. "Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information" Remote Sensing 12, no. 6: 1009. https://doi.org/10.3390/rs12061009

Feng X, He L, Cheng Q, Long X, Yuan Y. Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information. Remote Sensing. 2020; 12(6):1009. https://doi.org/10.3390/rs12061009

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Feng, X.; He, L.; Cheng, Q.; Long, X.; Yuan, Y. Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information. Remote Sens. 2020, 12, 1009. https://doi.org/10.3390/rs12061009

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.