Add to ORKGOptimization-based approaches for image deblurring and denoising on Graphics processing Units (GPU) are considered. In particular, a new GPU implementation of a recent gradient projection method for edge-preserving removal of Poisson noise is presented. The speedups over standard CPU implementations are evaluated on both synthetic data and astronomical and medical imaging problems
This paper presents a fast deblurring method that produces a deblurring result from a single image o...
International audienceThis paper focuses on the deblurring and denoising of Poisson noise contaminat...
This paper explores eective algorithms for the solution of numerical nonlinear optimization problems...
Optimization-based approaches for image deblurring and denoising onGraphics Processing Units (GPU) a...
Gradient type methods are widely used approaches for nonlinear programming in image processing, due ...
Gradient type methods are widely used approaches for nonlinearprogramming in image processing, due t...
This paper presents a graphics processing unit (GPU) implementation of a recently published augmente...
The ability of the modern graphics processors to operate on large matrices in parallel can be exploi...
This paper presents a graphics processing unit (GPU) implementation of a recently published augmente...
Several methods based on different image models have been proposed and developed for image denoising...
In this paper we propose a special gradient projection method for the image deblurring problem, in t...
The aim of this paper is to present a computational study on scaling techniques in gradient projecti...
We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method f...
In this paper we propose a special gradient projection method for the image deblurring problem, in ...
AbstractA parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU...
This paper presents a fast deblurring method that produces a deblurring result from a single image o...
International audienceThis paper focuses on the deblurring and denoising of Poisson noise contaminat...
This paper explores eective algorithms for the solution of numerical nonlinear optimization problems...
Optimization-based approaches for image deblurring and denoising onGraphics Processing Units (GPU) a...
Gradient type methods are widely used approaches for nonlinear programming in image processing, due ...
Gradient type methods are widely used approaches for nonlinearprogramming in image processing, due t...
This paper presents a graphics processing unit (GPU) implementation of a recently published augmente...
The ability of the modern graphics processors to operate on large matrices in parallel can be exploi...
This paper presents a graphics processing unit (GPU) implementation of a recently published augmente...
Several methods based on different image models have been proposed and developed for image denoising...
In this paper we propose a special gradient projection method for the image deblurring problem, in t...
The aim of this paper is to present a computational study on scaling techniques in gradient projecti...
We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method f...
In this paper we propose a special gradient projection method for the image deblurring problem, in ...
AbstractA parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU...
This paper presents a fast deblurring method that produces a deblurring result from a single image o...
International audienceThis paper focuses on the deblurring and denoising of Poisson noise contaminat...
This paper explores eective algorithms for the solution of numerical nonlinear optimization problems...