Browsing by Subject "Image recovery"

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    Parallel algorithms for the solution of large sparse inequality systems on distributed memory architectures
    (1998) Turna, Esma
    In this thesis, several parallel algorithms are proposed and utilized for the solution of large sparse linear inequality systems. The parallelization schemes are developed from the coarse-grain parallel formulation of the surrogate constraint method, based on the partitioning strategy: 1D partitioning and 2D partitioning. Furthermore, a third parallelization scheme is developed for the explicit minimization of the communication overhead in 1D partitioning, by using hypergraph partitioning. Utilizing the hypergraph model, the communication overhead is maintained via a global communication scheme and a local communication scheme. In addition, new algorithms that use the bin packing heuristic are investigated for efficient load balancing in uniform rowwise stripped and checkerboard partitioning. A general class of image recovery problems is formulated as a linear inequality system. The restoration of images blurred by so called point spread functions arising from effects such as misfocus of the photographic device, atmospheric turbulence, etc. is successfully provided with the developed parallel algorithms.
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    ItemOpen Access
    Restoration of space-variant global blurs caused by severe camera movements and coordinate distortions
    (IOP Science, 1998) Özaktaş, H.; Pınar, M. Ç.; Akgül, M.
    We show that a broad class of image recovery problems where an object undergoing an arbitrary two-dimensional, time- and space-variant, non-separable, nonlinear global coordinate distortion, is imaged for a certain duration, can be formulated as a system of linear inequalities. Since the system of inequalities arising in this context can be solved efficiently, our approach yields an effective method for solving this class of image recovery problems. A novel step size policy is introduced to accelerate the parallel surrogate constraint algorithm employed. The approach is illustrated by recovering an image severely blurred by the combined effects of translational and rotational motion and elliptic scaling.