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Hyperspectral imagery visualization using double layers
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DOI：10.1109/TGRS.2007.894922.png)
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摘要
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Displaying the abundant information contained in a hyperspectral image is a challenging problem. Almost any visualization approach reduces the information content. However, we want to maximize the amount of object or material information presented. A visualization approach that uses classification as an intermediate step may maximize the information transfer. In our research, we are particularly interested in the display of mixed-pixel classification results, since most pixels in a remotely sensed hyperspectral image are mixed pixels. In this paper, we propose a visualization technique that employs two layers to integrate the mixture information (i.e., endmembers and their abundances) in each pixel. Images can be displayed with any desired level of details.
Keyword:
hyperspectral imagery visualization
linear unmixing analysis
unsupervised classification
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IF:
8.6
论文数:
2.1W
被引数:
10.7W
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