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A Novel Variational Model with Strict Convexity for Multiplicative Noise Removal

机译:具有严格凸性的新型变分模型,用于乘法噪声拆除

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—In this paper, a novel variational model with strict convexity for removing multiplicative noise from images is proposed and studied. Firstly, by applying maximum likelihood estimation method and the Bayesian formulation, the variational model is derived. Then, we use an alternating minimization algorithm to find out the minimizer of the objective function, and prove the existence of the minimizer for the underlying variational problem in theory. Finally, Our experimental results show that the quality of images denoised by the proposed method is quite good, and the proposed model is superior to the existing key models in preventing the images from stair-casing, and in restoring more texture details of the denoised image.
机译:- 本文提出了一种具有严格凸性的新型变分模型,用于去除图像的乘法噪声。首先,通过应用最大似然估计方法和贝叶斯配方,得到变分模型。然后,我们使用交替的最小化算法来找出目标函数的最小化器,并证明理论上的基础变分问题的最小化器。最后,我们的实验结果表明,所提出的方法去噪的图像质量非常好,所提出的模型优于现有的关键模型,防止楼梯壳体的图像,以及恢复去噪图像的更多纹理细节。

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