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Blur and Contrast Invariant Fast Stereo Matching

  • Matteo Pedone
  • Janne Heikkilä
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5259)

Abstract

We propose a novel approach for estimating a depth-map from a pair of rectified stereo images degraded by blur and contrast change. At each location in image space, information is encoded with a new class of descriptors that are invariant to convolution with centrally symmetric PSF and to variations in contrast. The descriptors are based on local-phase quantization, they can be computed very efficiently and encoded in a limited number of bits. A simple measure for comparing two encoded templates is also introduced. Results show that, the proposed method can represent a cheap but still effective way for estimating disparity maps from degraded images, without making restrictive assumptions; these advantages make it attractive for practical applications.

Keywords

Local Descriptor Stereo Match Stereo Pair Degraded Image Contrast Change 
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 2008

Authors and Affiliations

  • Matteo Pedone
    • 1
  • Janne Heikkilä
    • 1
  1. 1.Department of Electrical and Information EngineeringUniversity of OuluFinland

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