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On the study of fusion techniques for bad geological remote sensing image

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Abstract

One of the crucial steps in the fusion of remote sensing image is the selection of proper fusion techniques. In this paper, we focused on the bad geology, such as desert, permafrost, saltmarsh, etc., in Yuli Rob Village, Xinjiang Province. The selection of best band in remote sensing images is treated as a combinational optimization problem, and an optimum index factor method is proposed for the selection of best band in remote sensing images. Based on the analysis of general fusion techniques used in remote sensing image, three representative techniques, i.e., Gram-Schmidt, color normalized transformation, and principle component transformation are used for the fusion of bad geological remote sensing images. Experimental results indicated that the techniques used in this study improve the image spatial information, and they can maintain the spectral feature of multi-spectral images.

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Acknowledgments

This work was partly supported by the project of Multi-source Data Fusion Method Based on High Spatial Resolution RS, LiDAR and GPR (No. 2012FFB06403) and the project of Supporting Technology in Xinjiang Trunk Road Network Construction Demonstration Project (No. 2012196539).

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Authors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, 430074, China

    Xiang Li

  2. Engineering and Electronic Information Department, Wuhan University of Engineering Science, Wuhan, 430200, China

    Lingling Wang

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  1. Xiang Li
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  2. Lingling Wang
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Correspondence to Xiang Li.

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Li, X., Wang, L. On the study of fusion techniques for bad geological remote sensing image. J Ambient Intell Human Comput 6, 141–149 (2015). https://doi.org/10.1007/s12652-015-0255-1

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  • DOI: https://doi.org/10.1007/s12652-015-0255-1

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