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Blind deconvolution of blurred image by iterative algorithm

机译:迭代算法对模糊图像进行盲反卷积

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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.
机译:我们提出了一种基于最小化代价函数并将图像投影到满足非负约束和/或支持约束的图像空间上的盲反卷积方法。这些最小化和投影过程在此方法中迭代使用。本文介绍了该方法的基本概念和构造的算法。在计算机仿真结果中,表明成本函数单调下降。即使不使用支撑约束,也可以看到此稳定属性。但是,该算法需要大量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。还显示了克服这种停滞问题的方法。

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