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Iterative methods for image deblurring: A Matlab object-oriented approach. (English) Zbl 1048.65039
Summary: In iterative image restoration methods, implementation of efficient matrix vector multiplication, and linear system solves for preconditioners, can be a tedious and time consuming process. Different blurring functions and boundary conditions often require implementing different data structures and algorithms. A complex set of computational methods is needed, each likely having different input parameters and calling sequences. This paper describes a set of Matlab tools that hide these complicated implementation details. Combining the powerful scientific computing and graphics capabilities in Matlab, with the ability to do object-oriented programming and operator overloading, results in a set of classes that is easy to use, and easily extensible.
MSC:
65F22Ill-posedness, regularization (numerical linear algebra)
65F35Matrix norms, conditioning, scaling (numerical linear algebra)
94A08Image processing (compression, reconstruction, etc.)
68W30Symbolic computation and algebraic computation