• Mark Grundland
  • Neil A. Dodgson
Part of the Computational Imaging and Vision book series (CIVI, volume 32)


We present an automated algorithm for global contrast enhancement of images with multimodal histograms. To locate modes and valleys, histogram analysis is performed by kernel density estimation, a robust nonparametric statistical method. Histogram warping by monotonic splines pushes the modes apart, spreading them out more evenly across the dynamic range. This technique can assist in the contrast correction of images taken facing the light source.


Contrast Enhancement Gray Level Kernel Density Estimation Object Feature Histogram Equalization 
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 2006

Authors and Affiliations

  • Mark Grundland
    • 1
  • Neil A. Dodgson
    • 1
  1. 1.Computer LaboratoryUniversity of CambridgeCambridgeUnited Kingdom

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