Weighted total generalized variation model for Poisson noise removal

Directional Total Generalized Variation Regularization for Impulse Noise Removal

Multilevel algorithm for a Poisson noise removal model with total-variation regularization

Many commonly used models for the fundamental image processing task of noise removal can deal with Gaussian white noise. However such Gaussian models are not effective to restore images with Poisson noise, which is ubiquitous in certain applications. Recently Le-Chartrand-Asaki derived a new data-fitting term in the variational model for Poisson noise. This paper proposes a multilevel algorithm...

Nonlinear total variation based noise removal algorithms

A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using the gradient-projection method. This amounts to solving a time dependent partial differential equation...

A New Total Variation Method for Multiplicative Noise Removal

where α1 and α2 are positive regularization parameters. The main advantage of using the new data fitting term ∑n2 i=1 ( [z]i + [g]iei ) is that its second derivative with respect to [z]i is equal to [g]i e−[z]i , therefore it implies that the new data fitting term is strictly convex for all z. Here we add a fitting term ||z −w||2 in the new minimization method. We can interpret the total variat...

PATIL, RAJWADE: POISSON NOISE REMOVAL FOR IMAGE DEMOSAICING 1 Poisson Noise Removal for Image Demosaicing

With increasing resolution of the sensors in camera detector arrays, acquired images are ever more susceptible to perturbations that appear as grainy artifacts called ‘noise’. In real acquisitions, the dominant noise model has been shown to follow the Poisson distribution, which is signal dependent. Most color image cameras today acquire only one out of the R, G, B values per pixel by means of ...