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http://dx.doi.org/10.7780/kjrs.2010.26.5.489

Noise Band Extraction of Hyperion Image using Quadtree Structure and Fractal Characteristic  

Chang, An-Jin (Department of Civil & Environmental Engineering, Seoul National University)
Kim, Yong-Il (Department of Civil & Environmental Engineering, Seoul National University)
Publication Information
Korean Journal of Remote Sensing / v.26, no.5, 2010 , pp. 489-495 More about this Journal
Abstract
Hyperspectral imaging obtains information with a wider wavelength range a large number of bands. However, a high correlation between each band, computation cost, and noise causes inaccurate results in cases of no pre-processing. The noises of band extraction and elimination positively necessary in hyperspectral imaging. Since the previous studies have used a characteristic the whole image, a local characteristic of the image is considered for the noise band extraction. In this study, the Quadtree, which is a data structure algorithm. and the fractal dimension are adopted for noise band extraction in Hyperion images. The fractal dimensions of the segments divided by the Quadtree structure are calculated, and variation is used. We focused on the extraction of random noise bands in Hyperion images and compared them with the reference data made by visual decisions. The proposed algorithm extracts the most bands, including random noises. It is possible to eliminate more than 30 noise bands, regardless of images.
Keywords
Quadtree; Fractal; Noise Band; Hyperspectral; Hyperion;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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