Please use this identifier to cite or link to this item:
https://doi.org/10.1109/IGARSS.2012.6351726
DC Field | Value | |
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dc.title | Implmentation of a covariance-based principal component analysis algorithm for hyperspectral imaging applications with multi-threading in both CPU and GPU | |
dc.contributor.author | Zhang, J. | |
dc.contributor.author | Lim, K.H. | |
dc.date.accessioned | 2014-11-28T07:57:45Z | |
dc.date.available | 2014-11-28T07:57:45Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | Zhang, J., Lim, K.H. (2012). Implmentation of a covariance-based principal component analysis algorithm for hyperspectral imaging applications with multi-threading in both CPU and GPU. International Geoscience and Remote Sensing Symposium (IGARSS) : 4264-4266. ScholarBank@NUS Repository. https://doi.org/10.1109/IGARSS.2012.6351726 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/112871 | |
dc.description.abstract | Principle component analysis (PCA) [1] is widely utilized in hyperspectral image analysis [3, 4, 5]. There are three major approaches of principle component analysis: singular value decomposition (SVD) [2], covariance-matrix and iterative method (NIPALS) [6, 7]. In our previous work [9], we have demonstrated the advantage of the GPU implementation of covariance method for medium-sized hyperspectral images. In this paper, we present an improvement which combines the multithreading in CPU, GPU and CUDA's graphics interoperability [8]. It is found that this combined framework approaches real-time processing much further. © 2012 IEEE. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IGARSS.2012.6351726 | |
dc.source | Scopus | |
dc.subject | CUDA | |
dc.subject | GPU | |
dc.subject | Hyperspectral | |
dc.subject | PCA | |
dc.subject | real-time | |
dc.type | Conference Paper | |
dc.contributor.department | CTR FOR REM IMAGING,SENSING & PROCESSING | |
dc.description.doi | 10.1109/IGARSS.2012.6351726 | |
dc.description.sourcetitle | International Geoscience and Remote Sensing Symposium (IGARSS) | |
dc.description.page | 4264-4266 | |
dc.description.coden | IGRSE | |
dc.identifier.isiut | 000313189404086 | |
Appears in Collections: | Staff Publications |
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