On Dimensionality Reduction for Indexing and Retrieval of Large-Scale Solar Image Data
This work investigates the applicability of several dimensionality reduction techniques for large-scale solar data analysis. Using a solar benchmark dataset that contains images of multiple types of phenomena, we investigate linear and nonlinear dimensionality reduction methods in order to reduce ou...
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| Veröffentlicht in: | Solar physics 2013-03, Vol.283 (1), p.113-141 |
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| container_end_page | 141 |
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| container_title | Solar physics |
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| creator | Banda, J. M. Angryk, R. A. Martens, P. C. H. |
| description | This work investigates the applicability of several dimensionality reduction techniques for large-scale solar data analysis. Using a solar benchmark dataset that contains images of multiple types of phenomena, we investigate linear and nonlinear dimensionality reduction methods in order to reduce our storage and processing costs and maintain a good representation of our data in a new vector space. We present a comparative analysis of several dimensionality reduction methods and different numbers of target dimensions by utilizing different classifiers in order to determine the degree of data dimensionality reduction that can be achieved with these methods, and to discover the method that is the most effective for solar images. After determining the optimal number of dimensions, we then present preliminary results on indexing and retrieval of the dimensionally reduced data. |
| doi_str_mv | 10.1007/s11207-012-0027-4 |
| format | Article |
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| issn | 0038-0938 1573-093X |
| language | eng |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Astrophysics and Astroparticles Atmospheric Sciences Data analysis Data reduction Image Processing in the Petabyte Era Physics Physics and Astronomy Scientific imaging Solar physics Space Exploration and Astronautics Space Sciences (including Extraterrestrial Physics |
| title | On Dimensionality Reduction for Indexing and Retrieval of Large-Scale Solar Image Data |
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