Iterative methods for image deblurring: a Matlab object-oriented approach

被引:194
作者
Nagy, JG [1 ]
Palmer, K [1 ]
Perrone, L [1 ]
机构
[1] Emory Univ, Dept Math & Comp Sci, Atlanta, GA 30322 USA
基金
美国国家科学基金会;
关键词
image restoration; ill-posed problem; regularization; Matlab; object-oriented programming; iterative methods; preconditioning;
D O I
10.1023/B:NUMA.0000027762.08431.64
中图分类号
O29 [应用数学];
学科分类号
070104 [应用数学];
摘要
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.
引用
收藏
页码:73 / 93
页数:21
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