Title :
Hyperspectral Imagery Visualization Using Double Layers
Author :
Cai, Shangshu ; Du, Qian ; Moorhead, Robert J., II
Author_Institution :
Mississippi State Univ., Mississippi State
Abstract :
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.
Keywords :
geophysical techniques; image classification; image processing; remote sensing; double layers; hyperspectral imagery visualization; material information; mixed-pixel classification; object amount maximization; remote sensing; Colored noise; Displays; Hyperspectral imaging; Hyperspectral sensors; Image analysis; Personal communication networks; Pixel; Principal component analysis; Student members; Visualization; Hyperspectral imagery visualization; linear unmixing analysis; unsupervised classification;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2007.894922