Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 739-746, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/739/2016/
doi:10.5194/isprs-archives-XLI-B7-739-2016
 
21 Jun 2016
THE OPTIMIZED BLOCK-REGRESSION-BASED FUSION ALGORITHM FOR PANSHARPENING OF VERY HIGH RESOLUTION SATELLITE IMAGERY
J. X. Zhang1, J. H. Yang1,2, and P. Reinartz2 1Chinese Academy of Surveying and Mapping (CASM), 100830 Beijing, China
2Remote Sensing Technology Institute, German Aerospace Center (DLR), 82234 Wessling, Germany
Keywords: Remote sensing, Satellite imagery, Very high resolution, Image fusion Abstract. Pan-sharpening of very high resolution remotely sensed imagery need enhancing spatial details while preserving spectral characteristics, and adjusting the sharpened results to realize the different emphases between the two abilities. In order to meet the requirements, this paper is aimed at providing an innovative solution. The block-regression-based algorithm (BR), which was previously presented for fusion of SAR and optical imagery, is firstly applied to sharpen the very high resolution satellite imagery, and the important parameter for adjustment of fusion result, i.e., block size, is optimized according to the two experiments for Worldview-2 and QuickBird datasets in which the optimal block size is selected through the quantitative comparison of the fusion results of different block sizes. Compared to five fusion algorithms (i.e., PC, CN, AWT, Ehlers, BDF) in fusion effects by means of quantitative analysis, BR is reliable for different data sources and can maximize enhancement of spatial details at the expense of a minimum spectral distortion.
Conference paper (PDF, 2009 KB)


Citation: Zhang, J. X., Yang, J. H., and Reinartz, P.: THE OPTIMIZED BLOCK-REGRESSION-BASED FUSION ALGORITHM FOR PANSHARPENING OF VERY HIGH RESOLUTION SATELLITE IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 739-746, doi:10.5194/isprs-archives-XLI-B7-739-2016, 2016.

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