IEEE Trans Image Process - Graph cuts for curvature based image denoising.

Tópicos

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Resumo

Minimization of total variation (TV) is a well-known method for image denoising. Recently, the relationship between TV minimization problems and binary MRF models has been much explored. This has resulted in some very efficient combinatorial optimization algorithms for the TV minimization problem in the discrete setting via graph cuts. To overcome limitations, such as staircasing effects, of the relatively simple TV model, variational models based upon higher order derivatives have been proposed. The Euler's elastica model is one such higher order model of central importance, which minimizes the curvature of all level lines in the image. Traditional numerical methods for minimizing the energy in such higher order models are complicated and computationally complex. In this paper, we will present an efficient minimization algorithm based upon graph cuts for minimizing the energy in the Euler's elastica model, by simplifying the problem to that of solving a sequence of easy graph representable problems. This sequence has connections to the gradient flow of the energy function, and converges to a minimum point. The numerical experiments show that our new approach is more effective in maintaining smooth visual results while preserving sharp features better than TV models.

Resumo Limpo

minim total variat tv wellknown method imag denois recent relationship tv minim problem binari mrf model much explor result effici combinatori optim algorithm tv minim problem discret set via graph cut overcom limit staircas effect relat simpl tv model variat model base upon higher order deriv propos euler elastica model one higher order model central import minim curvatur level line imag tradit numer method minim energi higher order model complic comput complex paper will present effici minim algorithm base upon graph cut minim energi euler elastica model simplifi problem solv sequenc easi graph represent problem sequenc connect gradient flow energi function converg minimum point numer experi show new approach effect maintain smooth visual result preserv sharp featur better tv model

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