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Correction published on 11 September 2012, see Sensors 2012, 12(9), 12374.

Open AccessArticle
Sensors 2008, 8(1), 520-528; doi:10.3390/s8010520

The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper

Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, China
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Author to whom correspondence should be addressed.
Received: 17 October 2007 / Accepted: 23 January 2008 / Published: 24 January 2008
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Abstract

Image fusion is a useful tool in integrating a high-resolution panchromaticimage (HRPI) with a low-resolution multispectral image (LRMI) to produce a highresolutionmultispectral image (HRMI). To date, many image fusion techniques have beendeveloped to try to improve the spatial resolution of the LRMI to that of the HRPI with itsspectral property reliably preserved. However, many studies have indicated that thereexists a trade- off between the spatial resolution improvement and the spectral propertypreservation of the LRMI, and it is difficult for the existing methods to do the best in bothaspects. Based on one minimization problem, this paper mathematically analyzes thetradeoff in fusing remote sensing images. In experiment, four fusion methods are evaluatedthrough expanded spectral angle mapper (ESAM). Results clearly prove that all the testedmethods have this property. View Full-Text
Keywords: Image Fusion; Tradeoff Analysis; Spectral Preservation; Spatial Improvement; Expanded Spectral Angle Mapper (ESAM) Image Fusion; Tradeoff Analysis; Spectral Preservation; Spatial Improvement; Expanded Spectral Angle Mapper (ESAM)
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chen, S.; Su, H.; Zhang, R.; Tian, J.; Yang, L. The Tradeoff Analysis for Remote Sensing Image Fusion Using Expanded Spectral Angle Mapper. Sensors 2008, 8, 520-528.

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