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Color Image Restoration Based on Split Bregman Iteration Algorithm

机译:基于分裂Bregman迭代算法的彩色图像恢复

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摘要

In this paper, we modify the Split Bregman algorithm for color image restoration with the edge-preserving color image total variation model. The observed blurred images are assumed to be degraded by within channel and cross channel blurs. Our proposed algorithm is based on the Split Bregman process and simply requires Fast Fourier Transform in each iteration. Experimental comparisons using various types of blurs are reported, and the results show that, the proposed method significantly outperforms existing methods, such as the variable splitting alternative minimization algorithm and that adopted by MATLAB deblurring function, in terms of both objective signal to noise ratio and subjective vision quality. This demonstrates the efficiency of our proposed algorithms.
机译:在本文中,我们用边缘保留彩色图像总变化模型修改彩色图像恢复的分割bregman算法。 假设观察到的模糊图像通过通道和交叉沟道模糊来降低。 我们所提出的算法基于拆分Bregman进程,并且只需要在每次迭代中快速傅里叶变换。 报告了使用各种类型模糊的实验比较,结果表明,该方法显着优于现有的方法,例如可变分割替代最小化算法,并通过Matlab DeBlurring函数采用的目的信号到噪声比和 主观视觉质量。 这证明了我们所提出的算法的效率。

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