• Spectroscopy and Spectral Analysis
  • Vol. 33, Issue 3, 741 (2013)
WU Gui-ping1、*, XIAO Peng-feng2, FENG Xue-zhi2, and WANG Ke3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2013)03-0741-05 Cite this Article
    WU Gui-ping, XIAO Peng-feng, FENG Xue-zhi, WANG Ke. A Method of Object Detection for Remote Sensing Imagery Based on Spectral Space Transformation[J]. Spectroscopy and Spectral Analysis, 2013, 33(3): 741 Copy Citation Text show less

    Abstract

    Object detection is an intermediate link for remote sensing image processing, which is an important guarantee of remote sensing application and services aspects. In view of the characteristics of remotely sensed imagery in frequency domain, a novel object detection algorithm based on spectral space transformation was proposed in the present paper. Firstly, the Fourier transformation method was applied to transform the image in spatial domain into frequency domain. Secondly, the wedge-shaped sample and overlay analysis methods for frequency energy were used to decompose signal into different frequency spectrum zones, and the center frequency values of object’s features were acquired as detection marks in frequency domain. Finally, object information was detected with the matched Gabor filters which have direction and frequency selectivity. The results indicate that the proposed algorithm here performs better and it has good detection capability in specific direction as well.
    WU Gui-ping, XIAO Peng-feng, FENG Xue-zhi, WANG Ke. A Method of Object Detection for Remote Sensing Imagery Based on Spectral Space Transformation[J]. Spectroscopy and Spectral Analysis, 2013, 33(3): 741
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