• DocumentCode
    3690120
  • Title

    Pointwise approach on covariance matrix of oriented gradients for very high resolution image texture segmentation

  • Author

    Minh-Tan Pham;Grégoire Mercier;Julien Michel

  • Author_Institution
    TELECOM Bretagne - UMR CNRS 6285 Lab-STICC/CID
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1008
  • Lastpage
    1011
  • Abstract
    The present study involves an investigation of a pointwise approach on the feature covariance matrix to extract textu-ral features for very high resolution (VHR) satellite images. Indeed, our proposition is to construct the covariance matrix of oriented gradients using a non-dense approach based on characteristic points extracted from the image. This novel non-dense covariance descriptor is capable of not only capturing both radiometric and local geometric information from the image, but also encoding their joint distribution and correlation, which are effectively relevant for texture characterization and discrimination. In order to demonstrate the efficiency of the proposed descriptor, a texture-based image segmentation stage is carried out. First efforts on VHR panchromatic images using the proposed algorithm provide very promising and competitive results compared to classical methods.
  • Keywords
    "Covariance matrices","Image segmentation","Feature extraction","Image resolution","Visualization","Measurement","Histograms"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7325939
  • Filename
    7325939