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Image denoising with gradient projection

机译:梯度投影图像降噪

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摘要

Image denoising can be modeled as a minimization problem of L2 norm. This problem mostly is solved using L2-norm methods previously. However, L2-norm methods may smooth the results. In this paper, this problem is solved efficiently by gradient projection, in particular, minimization with L1-norm penalty as we proposed. A variable splitting technique is employed to make the L1 norm penalty function differentiable. We present a L1-norm gradient projection approach to image denoising problem where the denoising is subject to minimization with nonnegative constraints. Numerical experiments and comparisons demonstrate the effectiveness of the proposed approach.
机译:图像去噪可以作为L2规范的最小化问题进行建模。此问题主要通过先前使用L2-Norm方法来解决。但是,L2-Norm方法可以平滑结果。在本文中,通过梯度投影有效地解决了这个问题,特别是随着L1-NOM惩罚的最小化。采用可变分割技术来使L1规范惩罚功能可分辨。我们提出了一个L1-Norm梯度投影方法来实现脱景的图像去噪问题,其中脱落受到非负限制的最小化。数值实验和比较证明了提出的方法的有效性。

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