标题： 双网格参数选择方法及其在图像去模糊中的应用 显示英文标题

标题： Dual-grid parameter choice method with application to image deblurring

摘要： 变分正则化处理不适定逆问题基于最小化数据拟合项和正则化项之和。它们之间的平衡通过一个正的正则化参数来调整，但这个参数的自动选择在一般情况下仍然是一个未解决的问题。提出了一种新的参数选择方法，该方法基于使用两个略微不同的计算模型来解决相同的逆问题。由于噪声放大的原因，小参数值应该产生两个非常不同的重建结果。大参数值会导致两个相同但无意义的重建结果。最优参数值在极端之间通过匹配两个重建结果的图像相似性与预定义值来选择。新方法的有效性通过使用测量数据和两种不同正则化器进行图像去模糊处理得到了验证。 显示英文摘要

摘要： Variational regularization of ill-posed inverse problems is based on minimizing the sum of a data fidelity term and a regularization term. The balance between them is tuned using a positive regularization parameter, whose automatic choice remains an open question in general. A novel approach for parameter choice is introduced, based on the use of two slightly different computational models for the same inverse problem. Small parameter values should give two very different reconstructions due to amplification of noise. Large parameter values lead to two identical but trivial reconstructions. Optimal parameter is chosen between the extremes by matching image similarity of the two reconstructions with a pre-defined value. Efficacy of the new method is demonstrated with image deblurring using measured data and two different regularizers.