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Assessing the Performance of Independent Component Analysis in Remote Sensing Data Processing

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Abstract

Independent component analysis (ICA) is a novel method to be considered as a powerful type of analysis in the process of source signal separation. Based on the capabilities of this particular analysis, there will be a hypothesis of applying ICA in the image processing of remote sensing data. This paper aims to introduce the ability of ICA in contrasting and highlighting some area with potential of mineralization. Considering and applying ICA transformation on the ETM+ image of southern Masule, Iran has resulted in finding some favorable points for further investigation. Moreover, sampling program on the indicated area has led to identify some huge, unexpected lithology and dikes. ICA analysis is a robust method even in remote sensing data processing with the high speed and capabilities in separating source signals from noise.

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Authors and Affiliations

  1. Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran

    Raoof Gholami

  2. Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran

    Ali Moradzadeh

  3. Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran

    Mahyar Yousefi

Authors
  1. Raoof Gholami
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  2. Ali Moradzadeh
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  3. Mahyar Yousefi
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Correspondence to Raoof Gholami.

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Gholami, R., Moradzadeh, A. & Yousefi, M. Assessing the Performance of Independent Component Analysis in Remote Sensing Data Processing. J Indian Soc Remote Sens 40, 577–588 (2012). https://doi.org/10.1007/s12524-011-0189-9

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  • DOI: https://doi.org/10.1007/s12524-011-0189-9

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