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| Titel |
Block-based cloud classification with statistical features and distribution of local texture features |
| VerfasserIn |
H.-Y. Cheng, C.-C. Yu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 3 ; Nr. 8, no. 3 (2015-03-10), S.1173-1182 |
| Datensatznummer |
250116208
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| Publikation (Nr.) |
 copernicus.org/amt-8-1173-2015.pdf |
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| Zusammenfassung |
| This work performs cloud classification
on all-sky images. To deal with mixed cloud types in one image, we propose
performing block division and block-based classification. In addition to
classical statistical texture features, the proposed method incorporates
local binary pattern, which extracts local texture features in the feature
vector. The combined feature can effectively preserve global information as
well as more discriminating local texture features of different cloud types.
The experimental results have shown that applying the combined feature
results in higher classification accuracy compared to using classical
statistical texture features. In our experiments, it is also validated that
using block-based classification outperforms classification on the entire
images. Moreover, we report the classification accuracy using different
classifiers including the k-nearest neighbor classifier, Bayesian classifier,
and support vector machine. |
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