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Parameter estimation for image deblurring

机译:图像去模糊的参数估计

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摘要

Blurred images usually come from all kinds of imaging equipments, which may provide important prior information about the possible MTF models with unknown parameters. Based on this prior, we aim to estimate their corresponding parameters for image deblurring. From the fractal model of the original distinct image and the image degradation model, we firstly analyze the statistical character of the blurred image; and then we estimate the noise level by the high frequency energy of the blurred image. For the given MTF degradation model, we estimate the fractal parameters and the MTF parameters by Maximum Likelihood Estimation (MLE), which is achieved numerically by alternating optimization scheme.
机译:模糊图像通常来自各种成像设备,这些设备可能会提供有关参数未知的可能MTF模型的重要先验信息。基于此先验,我们旨在估计其对应的参数以进行图像去模糊。从原始清晰图像的分形模型和图像退化模型出发,我们首先分析了模糊图像的统计特征。然后我们通过模糊图像的高频能量来估计噪声水平。对于给定的MTF降级模型,我们通过最大似然估计(MLE)估计分形参数和MTF参数,这是通过交替优化方案以数值方式实现的。

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