An iterative regularization method for total variation-based image restoration
An iterative regularization method for total variation-based image restoration
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DOI：
10.1137/040605412
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发表时间：
2005-01-01
影响因子：
1.6
通讯作者：
Yin, WT
中科院分区：
文献类型：
--
作者：
Osher, S;Burger, M;Yin, WT
我们介绍了一种新的基于Bregman距离的反问题迭代正则化方法，特别是针对图像处理中出现的问题。我们的动机是利用全变分正则化的变分方法来恢复含有噪声和模糊的图像。我们得到了一般过程的严格收敛结果和有效的停止准则。去噪的数值结果似乎比标准模型有了显著的改善，去模糊/去噪的初步结果非常令人鼓舞。
We introduce a new iterative regularization procedure for inverse problems based on the use of Bregman distances, with particular focus on problems arising in image processing. We are motivated by the problem of restoring noisy and blurry images via variational methods by using total variation regularization. We obtain rigorous convergence results and effective stopping criteria for the general procedure. The numerical results for denoising appear to give significant improvement over standard models, and preliminary results for deblurring/denoising are very encouraging.