論文

2018年10月31日

Spatial resolution enhancement of optical images based on tensor decomposition

International Geoscience and Remote Sensing Symposium (IGARSS)
  • Kuniaki Uto
  • ,
  • Mauro Dalla Mura
  • ,
  • Jocelyn Chanussot

2018-July
開始ページ
8058
終了ページ
8061
記述言語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/IGARSS.2018.8518769

© 2018 IEEE There is an inevitable trade-off between spatial and spectral resolutions in optical remote sensing images. A number of data fusion techniques of multimodal images with different spatial and spectral characteristics have been developed to generate optical images with both spatial and spectral high resolution. Although some of the techniques take the spectral and spatial blurring process into account, there is no method that attempts to retrieve an optical image with both spatial and spectral high resolution, a spectral blurring filter and a spectral response simultaneously. In this paper, we propose a new framework of spatial resolution enhancement by a fusion of multiple optical images with different characteristics based on tensor decomposition. An optical image with both spatial and spectral high resolution, together with a spatial blurring filter and a spectral response, is generated via canonical polyadic (CP) decomposition of a set of tensors. Experimental results featured that relatively reasonable results were obtained by regularization based on nonnegativity and coupling.

リンク情報
DOI
https://doi.org/10.1109/IGARSS.2018.8518769
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85064180002&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85064180002&origin=inward

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