An Energy-Based Model for the Image Edge-Histogram Specification Problem

  • Authors:

  • Max Mignotte

  • Affiliations:

  • Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Faculté des Arts et des Sciences, Montréal, Canada

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 2012

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Abstract

In this correspondence, we present an original energy-based model that achieves the edge-histogram specification of a real input image and thus extends the exact specification method of the image luminance (or gray level) distribution recently proposed by Coltuc et al. Our edge-histogram specification approach is stated as an optimization problem in which each edge of a real input image will tend iteratively toward some specified gradient magnitude values given by a target edge distribution (or a normalized edge histogram possibly estimated from a target image). To this end, a hybrid optimization scheme combining a global and deterministic conjugate-gradient-based procedure and a local stochastic search using the Metropolis criterion is proposed herein to find a reliable solution to our energy-based model. Experimental results are presented, and several applications follow from this procedure.