Single-Image Motion Deblurring Using Normalized Nonlinear Diffusion Regularization

Guodong Wang, Zhenkuan Pan, Jie Xu, Qian Dong, Shixiu Zheng
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引用次数: 1

Abstract

Motion deblur is a very hot and hard research topic currently because it is an ill-posed problem. In this paper, we proposed using normalized nonlinear diffusion regularization for motion deblurring. To reduce the complexity of solving the deblurring equation, a fast method called Split method is used. Because the result derived from the energy function give the lowest cost, our method doesn't need any auxiliary method for solving the energy function besides multiscale implementation. Using the estimated kernel, the final clear image can be got by total variation method. Experiments demonstrate the validity of the proposed method.
使用归一化非线性扩散正则化的单像运动去模糊
运动去模糊是一个病态问题,是目前研究的热点和难点。本文提出了用归一化非线性扩散正则化进行运动去模糊。为了降低解去模糊方程的复杂性,采用了一种快速的方法——分割法。由于能量函数得到的结果成本最低,因此除了多尺度实现外,我们的方法不需要任何辅助方法来求解能量函数。利用估计的核,用全变分法得到最终的清晰图像。实验证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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