Energy Minimization Methods

Mila Nikolova
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Mila Nikolova: ENS Cachan, CNRS UniversSud

Chapter 5 in Handbook of Mathematical Methods in Imaging, 2011, pp 139-185 from Springer

Abstract: Abstract Energy minimization methods are a very popular tool in image and signalprocessing. This chapter deals with images defined on a discrete finite set. Energyminimization methods are presented from a nonclassical standpoint: weprovide analytical results on their minimizers that reveal salient featuresof the images recovered in this way, as a function of the shape of theenergy itself. The energies under consideration can be differentiable ornot, convex or not. Examples and illustrations corroborate the presentedresults. Applications that take benefit from these results are presented as well.

Keywords: Global Minimizer; Noisy Data; Homogeneous Region; Impulse Noise; Shrinkage Estimator (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1007/978-0-387-92920-0_5

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