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Octonion sparse representation for color and multispectral image processing

Srdan Lazendic (UGent) , Hendrik De Bie (UGent) and Aleksandra Pizurica (UGent)
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Abstract
A recent trend in color image processing combines the quaternion algebra with dictionary learning methods. This paper aims to present a generalization of the quaternion dictionary learning method by using the octonion algebra. The octonion algebra combined with dictionary learning methods is well suited for representation of multispectral images with up to 7 color channels. Opposed to the classical dictionary learning techniques that treat multispectral images by concatenating spectral bands into a large monochrome image, we treat all the spectral bands simultaneously. Our approach leads to better preservation of color fidelity in true and false color images of the reconstructed multispectral image. To show the potential of the octonion based model, experiments are conducted for image reconstruction and denoising of color images as well as of extensively used Landsat 7 images.
Keywords
Sparse representations, Octonions, Multispectral imaging, Landsat 7

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Chicago
Lazendic, Srdan, Hendrik De Bie, and Aleksandra Pizurica. 2018. “Octonion Sparse Representation for Color and Multispectral Image Processing.” In Proceedings of the 26th European Signal Processing Conference (EUSIPCO 2018), 608–612. EURASIP.
APA
Lazendic, Srdan, De Bie, H., & Pizurica, A. (2018). Octonion sparse representation for color and multispectral image processing. Proceedings of the 26th European Signal Processing Conference (EUSIPCO 2018) (pp. 608–612). Presented at the 2018 26th European Signal Processing Conference (EUSIPCO), EURASIP.
Vancouver
1.
Lazendic S, De Bie H, Pizurica A. Octonion sparse representation for color and multispectral image processing. Proceedings of the 26th European Signal Processing Conference (EUSIPCO 2018). EURASIP; 2018. p. 608–12.
MLA
Lazendic, Srdan, Hendrik De Bie, and Aleksandra Pizurica. “Octonion Sparse Representation for Color and Multispectral Image Processing.” Proceedings of the 26th European Signal Processing Conference (EUSIPCO 2018). EURASIP, 2018. 608–612. Print.
@inproceedings{8585246,
  abstract     = {A recent trend in color image processing combines the quaternion algebra with dictionary learning methods. This paper aims to present a generalization of the quaternion dictionary learning method by using the octonion algebra. The octonion algebra combined with dictionary learning methods is well suited for representation of multispectral images with up to 7 color channels. Opposed to the classical dictionary learning techniques that treat multispectral images by concatenating spectral bands into a large monochrome image, we treat all the spectral bands simultaneously. Our approach leads to better preservation of color fidelity in true and false color images of the reconstructed multispectral image. To show the potential of the octonion based model, experiments are conducted for image reconstruction and denoising of color images as well as of extensively used Landsat 7 images.},
  author       = {Lazendic, Srdan and De Bie, Hendrik and Pizurica, Aleksandra},
  booktitle    = {Proceedings of the 26th European Signal Processing Conference (EUSIPCO 2018)},
  isbn         = {9789082797015},
  issn         = {2076-1465},
  keyword      = {Sparse representations,Octonions,Multispectral imaging,Landsat 7},
  language     = {eng},
  location     = {Rome, Italy},
  pages        = {608--612},
  publisher    = {EURASIP},
  title        = {Octonion sparse representation for color and multispectral image processing},
  url          = {http://dx.doi.org/10.23919/eusipco.2018.8553272},
  year         = {2018},
}

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