Single-color image motion deblurring using MTV model

Hong Zhang, Guodong Wang, Nan Wu, Guojia Hou, Zhimei Zhang
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Abstract

Image blind restoration has been a significant subject in various application fields. In the paper, we mainly studied the color image. In the process of converting color image into gray image will result in the loss of information because color image has different channels. In order to solve blind deconvolution of color image effectively, we present a method that estimates kernel result from three channels of color image directly based on multiscale framework. And then we ues the Multichannel Total Variation (MTV) model to protect image edges. By using normalized hyper Laplacian prior term, our method can converge to the real solution. The final clear image can be gotten. Although the MTV model will increase the complexity of computation, The correctness of algorithm and the feasibility of methods are proved by experiments.
使用MTV模型的单色图像运动去模糊
图像盲恢复已成为各个应用领域的重要课题。本文主要研究的是彩色图像。在将彩色图像转换为灰度图像的过程中,由于彩色图像具有不同的通道,会造成信息的丢失。为了有效地解决彩色图像的盲反卷积问题,提出了一种基于多尺度框架的彩色图像三通道核结果直接估计方法。然后利用多通道全变分(MTV)模型对图像边缘进行保护。通过使用归一化超拉普拉斯先验项,我们的方法收敛到实解。最终得到清晰的图像。虽然MTV模型会增加计算复杂度,但实验证明了算法的正确性和方法的可行性。
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