Iterative choice of the optimal regularization parameter in TV image restoration
Iterative choice of the optimal regularization parameter in TV image restoration
复制标题
电视图像恢复中最优正则化参数的迭代选择
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
F. Peyrin
中科院分区：
文献类型：
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作者：
A. Toma;B. Sixou;F. Peyrin
提出了选择全变分正则化线性逆问题最优正则化参数的迭代方法。这种方法基于Morozov差异原理或该原理的阻尼版本，并基于数据项的近似模型函数。证明了正则化参数选择方法的理论收敛性。
We present iterative methods for choosing the optimal regularization parameter for linear inverse problems with Total Variation regularization. This approach is based on the Morozov discrepancy principle or on a damped version of this principle and on an approximating model function for the data term. The theoretical convergence of the method of choice of the regularization parameter is demonstrated.
The choice of the optimal parameter is refined with a Newton method. The efficiency of the method is illustrated on deconvolution and super-resolution experiments on different types of images. Results are provided for different levels of blur, noise and loss of spatial resolution. The damped Morozov discrepancy principle often outerperforms the approaches based on the classical Morozov principle and on the Unbiased Predictive Risk Estimator. Moreover, the proposed methods are fast schemes to select the best parameter for TV regularization.