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USEFULNESS OF THE FRACTAL DIMENSION IN THE CONTEXT OF HYPERSPECTRAL DATA DESCRIPTION

Michal Krupinski

First published: 2014-06-20https://doi.org/10.5593/sgem2014/b23/s10.046View metrics

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Title
USEFULNESS OF THE FRACTAL DIMENSION IN THE CONTEXT OF HYPERSPECTRAL DATA DESCRIPTION
Authors
Michal Krupinski
Proceedings
14th International Multidisciplinary Scientific GeoConference SGEM 2014, Geoinformatics, Remote Sensing, and Artificial Intelligence, Vol. 14, Book 2, Volume 3
Publisher
Stef92 Technology
Year
2014
Pages
Not available yet
ISSN
1314-2704
ISBN
Not available yet
Language
en
Publication type
Conference Paper
Proceedings volume
14th International Multidisciplinary Scientific GeoConference SGEM 2014, Geoinformatics, Remote Sensing, and Artificial Intelligence, Vol. 14, Book 2, Volume 3 · Issue Book 2, Volume 3
References14
  1. Drzewiecki W., Wawrzaszek A., Aleksandrowicz S., and Krupinski M. Initial evaluation of the applicability of multifractal measures as global content-based image descriptors, Proceedings of ESA-EUSC-JRC 8th Conference on Image Information Mining, Germany, 2012 pp 90-93, DOI: 10.2788/49465;

  2. Wawrzaszek A., Aleksandrowicz S., Krupinski M., Drzewiecki W. Influence of satellite image filtration on fractal and multifractal features in the context of land cover classification, Photogrammetrie, Fernerkundung, Geoinformation 2 014/2, Germany, 2014, pp 101-115, DOI: 10.1127/1432-8364/2014/0200;

  3. Drzewiecki W., Wawrzaszek A., Aleksandrowicz S., Krupinski M., and Bernat K. Comparison of selected textural features as global content-based descriptors of VHR satellite image, Geoscience and Remote Sensing Symposium (IGARSS), Australia, 2013, pp 4364 - 4366, DOI: 10.1109/IGARSS.2013.6723801;

  4. De Cola, L. Fractal analysis of a classified Landsat scene. Photogrammetric Engineering and Remote Sensing, 55, 1989, pp 601–610;

  5. Di Martino G., Iodice A., Riccio D., and Ruello G. Fractal parameters and SAR images, Radar Conference, RADAR '08, IEEE, Italy, 2008, pp 1-6, DOI: 10.1109/RADAR.2008.4720815;

  6. Dong P. Fractal signatures for multiscale processing of hyperspectral image data , Advances in Space Research 41, 2008, pp 1733–1743;

  7. Ziyong Z. Multifractal Based Hyperion Hyperspectral Data Mining, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010);

  8. Qiu H., Lam N., Quattrochi D., and Gamon J. Fractal characterization of hyperspectral imagery, Photogrammetric Engineering & Remote Sensing, Vol. 65 , No. 1, 1999, pp 63-71;

  9. Su H., Sheng Y., and Du P. A new band selection algorithm for hyperspectral data based on fractal dimension, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII, Part B7, China, 2008, pp 279- 283;

  10. Sarkar, N., and Chaudhuri B.B. An efficient differential box-counting approach to compute fractal dimension of image, IEEE Transactions on Systems, Man and Cybernetics 24, 1994, pp 115-120;

  11. Chaudhuri, B.B., and Sarkar N. Texture segmentation using fractal dimension, Pattern Analysis and Machine Intelligence, IEEE Transactions on 17(1), 1995, pp 72 – 77;

  12. Green R., Eastwood M., Sarture C., Chrien T., Aronsson M., Chippendale B., Faust J., Pavri B., Chovit C., Solis M., Olah M., and Williams O. Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Remote Sensing of Environment, Volume 65, Issue 3, 1998, ISSN 0034-4257, pp 227 -248, DOI: 10.1016/S0034-4257(98)00064-9;

  13. Sun., W., Xu G., Gong P., and Liang S. Fractal analysis of remotely sensed images: A review of methods and applications, International Journal of Remote Sensing 27(22), 2006, pp 4963–4990;

  14. Lopes R., and Betrouni N. Fractal and multifractal analysis: A review, Medical Image Analysis 13, 2009, pp 634–649.

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