杨敬娴, 郭喜庆, 孙鹏飞, 韩文钦, 解官宝. 集成学习法与双分裂Bregman正则化下的图像复原[J]. 微电子学与计算机, 2013, 30(12): 85-89,96.
引用本文: 杨敬娴, 郭喜庆, 孙鹏飞, 韩文钦, 解官宝. 集成学习法与双分裂Bregman正则化下的图像复原[J]. 微电子学与计算机, 2013, 30(12): 85-89,96.
YANG Jing-xian, GUO Xi-qing, SUN Peng-fei, HAN Wen-qin, XIE Guan-bao. Ensemble Learning and Bi-splitting Bregman Regularization for Image Deblurring[J]. Microelectronics & Computer, 2013, 30(12): 85-89,96.
Citation: YANG Jing-xian, GUO Xi-qing, SUN Peng-fei, HAN Wen-qin, XIE Guan-bao. Ensemble Learning and Bi-splitting Bregman Regularization for Image Deblurring[J]. Microelectronics & Computer, 2013, 30(12): 85-89,96.

集成学习法与双分裂Bregman正则化下的图像复原

Ensemble Learning and Bi-splitting Bregman Regularization for Image Deblurring

  • 摘要: 相机在拍摄过程中会受到多种模糊降质过程的影响,其中曝光过程中相机的抖动与散焦是极为常见的图像降质原因。针对自然图像梯度满足重尾分布的特性,利用混合高斯模型进行参数建模,并将模型参数作为先验知识,采用一种基于变分贝叶斯估计的集成学习法来估计降晰核。接着利用总变分正则化方法,提出了一种双分裂Bregman迭代算法,实现了在Bregman框架下的图像反卷积。采用本算法对两幅实际拍摄的模糊照片进行图像复原,并通过与目前的复原算法相比证明该算法能更加有效地去除图像模糊。

     

    Abstract: In the process of imaging,camera shake and defocusing during exposure are extremely common reasons for image degradation,and lead to objectionable image blur.Due to images of real-world scenes obey heavy-tailed distributions in their gradients,a mixture-of-Gaussians model is built to represent the distribution.Then Ensemble Learning approach based on the variational Bayesian estimation is applied to find the blur kernel.Given the kernel, the image deconvolution is completed using Total Variation Regularization, and bi-splitting Bregman iterative algorithm under Bregman framework is proposed in this paper.The experimental results show that this algorithm can effectively remove image blur compared to existing approach.

     

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