Presentation 2006-07-14
Winter Season Cloud Classification Using Self-Organizing Map
Tuomas KARNA, Mamoru KUBO, Ken-ichiro MURAMOTO,
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Abstract(in English) This paper introduces a method for cloud classification using NOAA AVHRR satellite images. AVHRR (Advanced Very High Resolution Radiometer) data consists of five-channel multi-spectral images. To reduce the dimensionality of the data, principal component analysis (PCA) is calculated for each channel separately. The most significant principal component values are then composed into an image feature vector. Finally, the feature vectors are clustered using self-organizing map (SOM). This method is applied for the study of winter season clouds in the Japan Sea area.
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Keyword(in English) Satellite Images / AVHRR / Principal Component Analysis / Self-Organizing Map / Image Clustering
Paper # IE2006-29,MVE2006-35
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Committee MVE
Conference Date 2006/7/7(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Winter Season Cloud Classification Using Self-Organizing Map
Sub Title (in English)
Keyword(1) Satellite Images
Keyword(2) AVHRR
Keyword(3) Principal Component Analysis
Keyword(4) Self-Organizing Map
Keyword(5) Image Clustering
1st Author's Name Tuomas KARNA
1st Author's Affiliation Department of Electrical and Communications Engineering, Helsinki University of Technology:Graduate School of Natural Science and Technology, Kanazawa University()
2nd Author's Name Mamoru KUBO
2nd Author's Affiliation Graduate School of Natural Science and Technology, Kanazawa University
3rd Author's Name Ken-ichiro MURAMOTO
3rd Author's Affiliation Graduate School of Natural Science and Technology, Kanazawa University
Date 2006-07-14
Paper # IE2006-29,MVE2006-35
Volume (vol) vol.106
Number (no) 158
Page pp.pp.-
#Pages 5
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