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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Fast and robust deblurring method with multi-frame images based on PSF estimation and total variation optimization
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Fast and robust deblurring method with multi-frame images based on PSF estimation and total variation optimization

机译:基于PSF估计和总变化优化的多帧图像快速鲁棒去模糊方法

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摘要

Multi-frame blind restoration algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. In this paper, we proposed a new multi-frame method based on PSF estimate and TV regularization. Our algorithm consists of first simplifying the multi-frame MAP model through the identification of blur parameters for each frame image and then adding various penalty terms to speed up the convergence in deconvolution process obviously. Finally, an adaptive L_2/L_1 norm selection scheme is built to deal with various noise distributions. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently even under large noise and image blurring.
机译:多帧盲恢复算法通常具有收敛速度慢和对复杂噪声敏感的缺点。在本文中,我们提出了一种新的基于PSF估计和电视正则化的多帧方法。我们的算法包括首先通过识别每个帧图像的模糊参数来简化多帧MAP模型,然后添加各种惩罚项以明显加快反卷积过程的收敛速度。最后,建立了自适应L_2 / L_1范数选择方案来处理各种噪声分布。一系列实验结果表明,即使在较大的噪声和图像模糊的情况下,所提方法仍能可靠,有效地优于其他方法。

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