NPtool: a MATLAB software for nonnegative image restoration with Newton projection methods Several image restoration applications require the solution of nonnegatively constrained minimization problems whose objective function is typically constituted by the sum of a data fit function and a regularization function. Newton projection methods are very attractive because of their fast convergence, but they need an efficient implementation to avoid time consuming iterations. In this paper we present NPTool, a set of Matlab functions implementing Newton projection methods for image denoising and deblurring applications. They are specifically thought for two different data fit functions, the Least Squares function and the Kullback-Leibler divergence, and two regularization functions, Tikhonov and Total Variation, giving the opportunity of solving a large variety of restoration problems. The package is easily extensible to other linear or nonlinear data fit and regularization functions. Some examples of its use are included in the package and shown in this paper.
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References in zbMATH (referenced in 7 articles , 1 standard article )
Showing results 1 to 7 of 7.
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- Jiang, Le; Huang, Jin; Lv, Xiao-Guang; Liu, Jun: Alternating direction method for the high-order total variation-based Poisson noise removal problem (2015)
- Landi, G.: A modified Newton projection method for (\ell_1)-regularized least squares image deblurring (2015)
- Lv, Xiao-Guang; Song, Yong-Zhong; Li, Fang: An efficient nonconvex regularization for wavelet frame and total variation based image restoration (2015)
- Jiang, Le; Huang, Jin; Lv, Xiao-Guang; Liu, Jun: Restoring Poissonian images by a combined first-order and second-order variation approach (2013)
- Landi, Germana; Piccolomini, Elena Loli: NPtool: a MATLAB software for nonnegative image restoration with Newton projection methods (2013)