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An adaptive algorithm for image restoration using combined penalty functions

机译:使用组合罚函数的自适应图像恢复算法

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摘要

In this paper, we present an adaptive gradient based method to restore images degraded by the effects of both noise and blur. The approach combines two penalty functions. The first derivative of the Canny operator is employed as a roughness penalty function to improve the high frequency information content of the image and a smoothing penalty term is used to remove noise. An adaptive algorithm is used to select the roughness and smoothing control parameters. We evaluate our approach using the Richardson-Lucy EM algorithm as a benchmark. The results highlight some of the difficulties in restoring blurred images that are subject to noise and show that in this case an algorithm that uses a combined penalty function is able to produce better quality results.
机译:在本文中,我们提出了一种基于自适应梯度的方法来还原由于噪声和模糊影响而退化的图像。该方法结合了两个惩罚函数。将Canny算子的一阶导数用作粗糙度惩罚函数以改善图像的高频信息内容,并使用平滑惩罚项来消除噪声。自适应算法用于选择粗糙度和平滑控制参数。我们使用Richardson-Lucy EM算法作为基准评估我们的方法。结果突出显示了还原受噪声影响的模糊图像的一些困难,并表明在这种情况下,使用组合惩罚函数的算法能够产生更好的质量结果。

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