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Information Technologies and Control

The Journal of Institute of Information and Communication Technologies of Bulgarian Academy of Sciences

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1312-2622
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Pre-Processing of Hyperspectral Images Using Nonlinear Filters

V. Behar
  • Corresponding author
  • Institute of Information and Communication Technologies, BAS 25A Acad. G. Bonchev St., 1113 Sofia, Bulgaria
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/ V. Bogdanova
Published Online: 2014-06-17 | DOI: https://doi.org/10.2478/itc-2013-0002

Abstract

In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6

Keywords: Hyperspectral imaging; random field simulation; edgepreserving filtration

References

  • 1. AVIRIS: Airborne Visible Infrared Imaging Spectrometer. http://aviris.jpl.nasa.gov.Google Scholar

  • 2. Manolakis, D., D. Marden, G. Shaw. Hyperspectral Image Processing for Automatic Target Detection Applications. - Lincoln Laboratory Journal, 14, 2003, No. 1,79-116.Google Scholar

  • 3. Ferwerda, J. G. Charting the Quality of Forage: Measuring and Mapping the Variation of Chemical Components in Foliage with Hyperspectral Remote Sensing. - ITC Dissertation, Wageningen University, 126, 2005, 166.Google Scholar

  • 4. Tilling, A. K., et al. Remote Sensing to Detect Nitrogen and Water Stress in Wheat. The Australian Society of Agronomy, 2006.Google Scholar

  • 5. Kamaruzaman, J. Precision Forestry Using Airborne Hyperspectral Imaging Sensor. - Journal of Agricultural Science, 1, 2009, No. 1, 142-147.Google Scholar

  • 6. Ustin, S., D. Roberts, J. Gamon, G. Asner, R. Green. Using Imaging Spectroscopy for Study Ecosystem Processes and Properties. - BioScience, 54, 2004, No. 6, 523-534.CrossrefGoogle Scholar

  • 7. Funk, C., J. Theiler, D. Roberts, C. Borel. Clustering to Improve Matched Filter Detection of Weak Gas Plumes in Hyperspectral Thermal Imagery. - IEEE Trans. on Geoscience and Remote Sensing, 39, 2001, No. 7, 1410-1420.Google Scholar

  • 8. Nagao, M., T. Matsuyama. Edge-preserving Smoothing Filters. - Computer Graphics and Image Processing, 9, 1979, No. 4, 394-407.CrossrefGoogle Scholar

  • 9. Ramponi, G. The Rational Filter for Image Processing. - IEEE Signal Processing Letters, 3, 1996, No. 3, 63-65.CrossrefWeb of ScienceGoogle Scholar

  • 10. Kroner, S., G. Ramponi, Edge Preserving Noise Smoothing with an Optimized Cubic Filter. Proc. COST-254 Workshop, Ljubljana, 1998, 19-21.Google Scholar

  • 11. Aurich, V., J. Weule. Non-Linear Gaussian Filters Performing Edge Preserving Diffusion. 17th DAGM Symposium, Bielefeld, 1995, 538-545.Google Scholar

  • 12. Yu, Y. Speckle Reducing Anisotropic Diffusion. - IEEE Trans. Imag. Proc., 11, 2002, 1260-1270.Google Scholar

  • 13. Sun, O., A. Hossack, J. Tang, S. Acton. Speckle Reducing Anisotropic Diffusion for 3D Ultrasound Images. - Computerized Medical Imaging and Graphics, 28, 2004, 461-470.CrossrefGoogle Scholar

  • 14. Stefan, D. Prostate Ultrasound Image Processing. - Spring, 13, 2007, No. 3, 20-23.Google Scholar

  • 15. Aiazzi, B., L. Alparone, A. Barducci, S. Baronti, P. Marcoionni, I. Pippi, M. Selva. Noise Modelling and Estimation of Hyperspectral Data from Airborne Imaging Spectrometers. - Annals of Geophysics, 49, 2006, No. 1, 1-9.Google Scholar

About the article

Received: 2013-10-15

Published Online: 2014-06-17

Published in Print: 2013-03-01


Citation Information: Information Technologies and Control, Volume 11, Issue 1, Pages 8–13, ISSN (Online) 1312-2622, DOI: https://doi.org/10.2478/itc-2013-0002.

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© 2014. This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. BY-NC-ND 3.0

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