MULTI-RESOLUTION SPATIAL UNMIXING FOR MERIS AND LANDSAT IMAGE FUSION

被引：4

作者：

Amoros-Lopez, J. ^{[1
]}

Gomez-Chova, L. ^{[1
]}

Guanter, L. ^{[2
]}

Alonso, L. ^{[1
]}

Moreno, J. ^{[1
]}

Camps-Valls, G. ^{[1
]}

机构：

[1] Univ Valencia, IPL, E-46003 Valencia, Spain

[2] Free Univ Berlin, Inst Space Sci, Berlin, Germany

来源：

2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年

关键词：

Multi-resolution; data fusion; spatial unmixing; sub-pixel; Landsat TM; MERIS;

D O I：

10.1109/IGARSS.2010.5649142

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Nowadays, the increasing quantity of applications using images from Earth Observation satellites makes demanding better spatial, spectral and temporal resolutions. Nevertheless, due to the technical constraint of a trade off between spatial and spectral resolutions, and between spatial resolution and coverage, high spatial resolution is related with low spectral and temporal resolutions and vice versa. Data fusion methods are a good solution to combine information from multiple sensors in order to obtain image products with better characteristics. In this paper, we propose an image fusion approach based on a multi-resolution and multi-source unmixing. The proposed methodology yields a composite image with the spatial resolution of the higher resolution image (downscaling) while retaining the spectral and temporal characteristics of the medium spatial resolution image. The approach is tested in the specific cases of ENVISAT/MERIS and Landsat/TM instruments, but is general enough to be applied to other sensor combination.

引用

页码：3672 / 3675

页数：4

共 7 条

[1] Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land [J].