In this paper, we propose a general algorithm for image denoising when no a priori information on the noise is available. The image denoising problem is formulated as an inequality constrained minimization problem where the objective is a general convex regularization functional and the right-hand side of the constraint depends on the noise norm and is not known. The proposed method is an iterative procedure which, at each iteration, automatically computes both an approximation of the noise norm and an approximate solution of the minimization problem. Experimental results demonstrate the effectiveness of the proposed automatic denoising procedure.
An algorithm for image denoising with automatic noise estimate
LANDI, GERMANA;LOLI PICCOLOMINI, ELENA
2009
Abstract
In this paper, we propose a general algorithm for image denoising when no a priori information on the noise is available. The image denoising problem is formulated as an inequality constrained minimization problem where the objective is a general convex regularization functional and the right-hand side of the constraint depends on the noise norm and is not known. The proposed method is an iterative procedure which, at each iteration, automatically computes both an approximation of the noise norm and an approximate solution of the minimization problem. Experimental results demonstrate the effectiveness of the proposed automatic denoising procedure.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
