Performance Evaluation of Multiresolution Methods in Disparity Estimation

  • Dibyendu Mukherjee
  • Gaurav Bhatnagar
  • Q. M. Jonathan Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)


Disparity estimation from stereo imagery has gained substantial interest of research community from its commencement with the recent trend being the use of multiresolution methods. Existing multiresolution based methods are relatively independent and do not, in general, relate to a continuous progress in the research. As a result, the relative advantages and disadvantages of a particular multiresolution method in disparity estimation are hard to understand. Present work is an effort to put different multiresolution methods together to highlight their expediency and suitability along with the comparison to get a better understanding. Three different frameworks are used having different strengths and limitations followed by the comparison in the terms of time complexity, quality of matching and effect of different levels of decomposition. Qualitative and quantitative results have been provided for four types of standard multiresolution methods.


Stereo Match Disparity Estimation Detail Part Contourlet Transform Stereo Match Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Dibyendu Mukherjee
    • 1
  • Gaurav Bhatnagar
    • 1
  • Q. M. Jonathan Wu
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of WindsorWindsorCanada

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