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A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

机译:用乘法噪声恢复模糊图像的凸变分模型

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摘要

In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees the uniqueness of the solution and the stabilization of the algorithm. For solving the new convex variational model, a primal-dual algorithm is proposed, and its convergence is studied. The paper ends with a report on numerical tests for the simultaneous deblurring and denoising of images subject to multiplicative noise. A comparison with other methods is provided as well.
机译:在本文中,提出了一种新的变分模型,该模型可以用模糊噪声恢复模糊图像。基于噪声的统计特性,利用二次惩罚函数技术在温和条件下获得严格的凸模型,从而保证了解的唯一性和算法的稳定性。为了解决新的凸变分模型,提出了一种原始对偶算法,并对其收敛性进行了研究。本文最后以数值测试报告为例,该测试旨在对倍增噪声下的图像同时进行去模糊和去噪。还提供了与其他方法的比较。

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