Open Access
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
Article Number 03070
Number of page(s) 4
Section Digital Signal and Image Processing
Published online 19 June 2018
  1. Ingram, R. N., et al., International Journal of Remote Sensing 25(22), An automatic nonlinear correlation approach for processing of hyperspectral images. 4981-4998. (2004) [Google Scholar]
  2. Du, Q., et al., IEEE Geoscience and Remote Sensing Letters 6(4), Segmented Principal Component Analysis for Parallel Compression of Hyperspectral Imagery. 713-717. (2009) [Google Scholar]
  3. Plaza, A., et al., Remote Sensing of Environment 113, Recent advances in techniques for hyperspectral image processing. S110-S122. (2009) [Google Scholar]
  4. Plaza, A., et al., Ieee Signal Processing Magazine 28(3), Parallel Hyperspectral Image and Signal Processing. (2011) [Google Scholar]
  5. Zhao, X. and X. Qiao, Spectral Characteristics Research of the Hyperspectral Image Based on the Correlation Matrix. Information Science and Engineering (ISISE), 2012 International Symposium on. (2012) [Google Scholar]
  6. Santos, L., et al. Journal of Applied Remote Sensing 7, Lossy hyperspectral image compression on a graphics processing unit: parallelization strategy and performance evaluation. (2013) [Google Scholar]
  7. Taher, A., et al., Hyperspectral image segmentation using a cooperative nonparametric approach. Image and Signal Processing for Remote Sensing Xix. L. Bruzzone. 8892. (2013) [Google Scholar]
  8. Santos, L., et al., Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(2), Highly-Parallel GPU Architecture for Lossy Hyperspectral Image Compression. 670-681. (2013) [Google Scholar]

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