基于迭代算法的模糊图像盲反卷积

T. Takahashi, H. Takajo
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引用次数: 2

摘要

我们提出了一种基于代价函数的最小化和图像在满足非负性约束和/或支持约束的图像空间上的投影的盲反卷积方法。在该方法中迭代地使用这些最小化和投影过程。本文给出了该方法的基本概念和构造的算法。计算机仿真结果表明,代价函数是单调递减的。即使在不使用支撑约束的情况下,也可以看到这种稳定特性。然而,该算法需要大量的迭代才能收敛到要检索的真实图像,并且有时会遇到停滞问题。文中还提出了一种克服停滞问题的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind deconvolution of blurred image by iterative algorithm
We propose a blind deconvolution method based on the minimization of a cost function and the projection of an image onto the image space satisfying nonnegativity constraint and/or support constraint. These minimization and projection procedures are used iteratively in this method. The basic concept of this method and the constructed algorithm are shown in this paper. In computer simulation results, it is shown that the cost function decreased monotonically. This stable property was seen even when the support constraint was not used. However, this algorithm needs a lot of iterations for the convergence to the true image to be retrieved, and is sometimes suffered from the stagnation problem. A method to overcome this stagnation problem is also shown.
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