3 research outputs found
Limited-memory scaled gradient projection methods for real-time image deconvolution in microscopy
Gradient projection methods have given rise to effective tools for image
deconvolution in several relevant areas, such as microscopy, medical imaging
and astronomy. Due to the large scale of the optimization problems arising
in nowadays imaging applications and to the growing request of real-time
reconstructions, an interesting challenge to be faced consists in designing
new acceleration techniques for the gradient schemes, able to preserve the
simplicity and low computational cost of each iteration. In this work we
propose an acceleration strategy for a state of the art scaled gradient
projection method for image deconvolution in microscopy. The acceleration
idea is derived by adapting a step-length selection rule, recently
introduced for limited-memory steepest descent methods in unconstrained
optimization, to the special constrained optimization framework arising in
image reconstruction. We describe how important issues related to the
generalization of the step-length rule to the imaging optimization problem
have been faced and we evaluate the improvements due to the acceleration
strategy by numerical experiments on large-scale image deconvolution problems
Iterative regularization algorithms for constrained image deblurring on graphics processors
The ability of the modern graphics processors to operate on large matrices in parallel can be exploited for solving constrained image deblurring problems in a short time.
In particular, in this paper we propose the parallel implementation of two iterative regularization methods: the well known expectation maximization algorithm and a recent scaled
gradient projection method. The main differences between the considered approaches and their impact on the parallel implementations are discussed. The effectiveness of the parallel
schemes and the speedups over standard CPU implementations are evaluated on test problems arising from astronomical images
Iterative regularization algorithms for constrained image deblurring on graphics processors
Image deblurring, Scaled gradient projection method, Graphics processing units,