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Variable exponent functionals in image restoration

机译:图像恢复中的可变指数功能

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摘要

We study a functional with variable exponent, 1 < p(x) <= 2, which provides a model for image denoising and restoration. Here p(x) is defined by the gradient information in the observed image. The diffusion derived from the proposed model is between total variation based regularization and Gaussian smoothing. The diffusion speed of the corresponding heat equation is tuned by the variable exponent p(x). The minimization problem and its associated flow in a weakened formulation are discussed. The existence, uniqueness, stability and long-time behavior of the proposed model are established in the variable exponent functional space W-1,W-p(x). Experimental results illustrate the effectiveness of the model in image restoration.
机译:我们研究了一个变量指数为1 (x)<= 2的函数,它为图像降噪和恢复提供了模型。在此,p(x)由观察图像中的梯度信息定义。从提出的模型得出的扩散值介于基于总变化的正则化和高斯平滑之间。相应的热方程的扩散速度通过变量指数p(x)进行调整。讨论了最小化问题及其在弱化配方中的相关流动。在可变指数函数空间W-1,W-p(x)中建立了所提出模型的存在性,唯一性,稳定性和长期行为。实验结果说明了该模型在图像复原中的有效性。

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