We report here a principled method for setting the regularization parameter in total variation filtering, that is based on the analysis of the distribution of the gray levels on the noisy image. We also report the results of an experimental investigation of the application of this framework to very low photon count digital radiography that shows the effectiveness of the method in denoising such images. Total variation regularization leads to a non-linear optimization problem that is solved here with a new generation adaptive first order method. Results suggest a further investigation of both the convergence criteria and/or the scheduling of the optimization parameters of this method.

Denoising of digital radiographic images with automatic regularization based on total variation / M. Lucchese, N.A. Borghese - In: Image Analysis and Processing – ICIAP 2009 : 15th international conference, Vietri sul Mare, Italy, September 8-11, 2009 : proceedings / [a cura di] P.Foggia, C.Sansone, M.Vento. - Berlin : Springer, 2009 Aug. - ISBN 9783642041457. - pp. 711-720 (( Intervento presentato al 15. convegno International Conference on Image Analysis and Processing tenutosi a Vietri sul Mare, Italy nel 2009 [10.1007/978-3-642-04146-4_76].

Denoising of digital radiographic images with automatic regularization based on total variation

N.A. Borghese
Ultimo
2009

Abstract

We report here a principled method for setting the regularization parameter in total variation filtering, that is based on the analysis of the distribution of the gray levels on the noisy image. We also report the results of an experimental investigation of the application of this framework to very low photon count digital radiography that shows the effectiveness of the method in denoising such images. Total variation regularization leads to a non-linear optimization problem that is solved here with a new generation adaptive first order method. Results suggest a further investigation of both the convergence criteria and/or the scheduling of the optimization parameters of this method.
Digital radiography ; total variation filtering ; regularization ; Bayesian filtering ; gradient descent minimization
Settore INF/01 - Informatica
ago-2009
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/154576
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