Statistical Multisensor Image Segmentation in Complex Wavelet Domains

  • Tao Wan
  • Zengchang Qin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6979)


We propose an automated image segmentation algorithm for segmenting multisensor images, in which the texture features are extracted based on the wavelet transform and modeled by generalized Gaussian distribution (GGD). First, the image is roughly segmented into textured and non-textured regions in the dual-tree complex wavelet transform (DT-CWT) domain. A multiscale segmentation is then applied to the resulting regions according to the local texture characteristics. Finally, a novel statistical region merging algorithm is introduced by measuring a Kullback-Leibler distance (KLD) between estimated GGD models for the neighboring segments. Experiments demonstrate that our algorithm achieves superior segmentation results.


multisensor image segmentation statistical modeling complex wavelets 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tao Wan
    • 1
  • Zengchang Qin
    • 1
    • 2
  1. 1.Robotics InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Intelligent Computing and Machine Learning Lab, School of ASEEBeihang UniversityBeijingChina

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