6533b85dfe1ef96bd12be9d4

RESEARCH PRODUCT

Multi-resolution spatial unmixing for MERIS and Landsat image fusion

J Amoros-lopezL Gomez-chovaL GuanterL AlonsoJ MorenoG Camps-vallsIeee

subject

Image fusionGeographic information systemPixelComputer sciencebusiness.industryResolution (electron density)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSensor fusionComposite image filterComputer Science::Computer Vision and Pattern RecognitionbusinessImage resolutionRemote sensingDownscaling

description

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. © 2010 IEEE.

yearjournalcountryeditionlanguage
2016-07-282010 IEEE International Geoscience and Remote Sensing Symposium
https://doi.org/10.1109/igarss.2010.5649142