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We investigate a constrained version of simultaneous iterative reconstruction techniques(SIRT) from the general viewpoint of projected gradient methods. This connection enable us to assess the computational merit of this algorithm class. We borrow a leaf from numerical optimization to cope with the slow convergence of projected gradient methods and propose an acceleration procedure based on the spectral gradient choice of steplength as in  and a nonmonotone strategy [17,4]. We compare these schemes and present numerical experiments on some algebraic image reconstruction models with sparsity constraints, with particular attention to tomographic particle image reconstruction. The performance of both constrained SIRT and nonmonotone spectral projected gradient approach is illustrated for several constraining strategies.
|Date Deposited:||28. May 2009 07:36|
|Faculties / Institutes:||Service facilities > Interdisciplinary Center for Scientific Computing|
|Uncontrolled Keywords:||SIRT, constraining strategies , spectral projected gradient , simplex projections , tomographic particle image reconstruction|