Lossy Compression of Hyperspectral Images Using Online Learning Based Sparse Coding
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Date
2014
Authors
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Publisher
Ieee
Open Access Color
Green Open Access
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No
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Abstract
A lossy hyperspectral image compression method is proposed using online learning based sparse coding. The least number of coefficients are obtained to represent hyperspectral images by applying the sparse coding algorithm which is based on a dicriminative online dictionary learning method. Results indicate that a pre-analysis of the number of non-zero dictionary elements may help in improving the overall compression quality.
Description
Toreyin, Behcet Ugur/0000-0003-4406-2783
ORCID
Keywords
Sparse Coding, Hyperspectral Imagery, Anomaly Detection, Online Learning
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
Ulku, Irem; Toreyin, B. Ugur, "Lossy Compression of Hyperspectral Images Using Online Learning Based Sparse Coding", International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), (2014).
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OpenCitations Citation Count
3
Source
International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) -- NOV 01-02, 2014 -- Paris, FRANCE
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1
End Page
5
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CrossRef : 3
Scopus : 5
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5
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1
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