Color Image Restoration Based on Split Bregman Iteration Algorithm

Yi Li-ya, Xiaolei Lu, Furong Wang
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Abstract

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.
基于分裂Bregman迭代算法的彩色图像恢复
本文采用保持边缘的彩色图像总变分模型,对分割Bregman彩色图像恢复算法进行改进。假设观察到的模糊图像被信道内模糊和跨信道模糊所退化。我们提出的算法是基于分裂Bregman过程,只需在每次迭代中进行快速傅立叶变换。实验结果表明,本文提出的方法在客观信噪比和主观视觉质量方面都明显优于现有方法,如变量分割替代最小化算法和MATLAB去模糊函数所采用的去模糊算法。这证明了我们提出的算法的有效性。
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