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http://dx.doi.org/10.7780/kjrs.2006.22.4.275

The Removal of Noisy Bands for Hyperion Data using Extrema  

Han, Dong-Yeob (School of Civil, Urban & Geo-System Engineering, Seoul National University)
Kim, Dae-Sung (School of Civil, Urban & Geo-System Engineering, Seoul National University)
Kim, Yong-Il (School of Civil, Urban & Geo-System Engineering, Seoul National University)
Publication Information
Korean Journal of Remote Sensing / v.22, no.4, 2006 , pp. 275-284 More about this Journal
Abstract
The noise sources of a Hyperion image are mainly due to the atmospheric effects, the sensor's instrumental errors, and A/D conversion. Though uncalibrated, overlapping, and all deep water absorption bands generally are removed, there still exist noisy bands. The visual inspection for selecting clean and stable processing bands is a simple practice, but is a manual, inefficient, and subjective process. In this paper, we propose that the extrema ratio be used for noise estimation and unsupervised band selection. The extrema ratio was compared with existing SNR and entropy measures. First, Gaussian, salt and pepper, and Speckle noises were added to ALI (Advanced Land Imager) images with relatively low noises, and the relation of noise level and those measures was explored. Second, the unsupervised band selection was performed through the EM (Expectation-Maximization) algorithm of the measures which were extracted from a Hyperion images. The Hyperion data were classified into 5 categories according to the image quality by visual inspection, and used as the reference data. The experimental result showed that the extrema ratio could be used effectively for band selection of Hyperion images.
Keywords
Hyperion; Band Selection; Extrema Ratio; Noise Estimation; EM Algorithm;
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Times Cited By KSCI : 1  (Citation Analysis)
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