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A Variational Method for the Optimization of Tone Mapping Operators

  • Praveen Cyriac
  • Thomas Batard
  • Marcelo Bertalmío
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)

Abstract

Given any metric that compares images of different dynamic range, we propose a method to reduce their distance with respect to this metric. The key idea is to consider the metric as a non local operator. Then, we transform the problem of distance reduction into a non local variational problem. In this context, the low dynamic range image having the smallest distance with a given high dynamic range is the minimum of a suitable energy, and can be reached through a gradient descent algorithm. Dealing with an appropriate metric, we present an application to Tone Mapping Operator (TMO) optimization. We apply our gradient descent algorithm, where the initial conditions are Tone Mapped (TM) images. Experiments show that our algorithm does reduce the distance of the TM images with the high dynamic range source images, meaning that our method improves the corresponding TMOs.

Keywords

Tone mapping Dynamic range independent metric Contrast distortion Variational methods 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Praveen Cyriac
    • 1
  • Thomas Batard
    • 1
  • Marcelo Bertalmío
    • 1
  1. 1.Department on Information and Communication TechnologiesUniversitat Pompeu FabraBarcelonaSpain

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