title: An energy-based model for the image edge-histogram specification problem.
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.
authors.forename: Max
authors.initials: M
authors.lastname: Mignotte
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted