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A Knife-edge Input Point Spread Function Estimation Method for Document Images

机译:文档图像的刀刃输入点扩展功能估计方法

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In this paper the progress of document image Point Spread Function (PSF) estimation will be presented. At the beginning of the paper, an overview of PSF estimation methods will be introduced and the reason why knife-edge input PSF estimation method is chosen will be explained. Then in the next section, the knife-edge input PSF estimation method will be detailed. After that, a simulation experiment is performed in order to verify the implemented PSF estimation method. Based on the simulation experiment, in next section we propose a procedure that makes automatic PSF estimation possible. A real document image is firstly taken as an example to illustrate the procedure and then be restored with the estimated PSF and Lucy-Richardson deconvolution method, and its OCR accuracy before and after deconvolution will be compared. Finally, we conclude the paper with the outlook for the future work.
机译:本文将呈现文档图像点扩展功能(PSF)估计的进展。在本文开始时,将介绍PSF估计方法的概述,并解释选择刀边缘输入PSF估计方法的原因。然后在下一节中,将详细介绍刀刃输入PSF估计方法。之后,进行仿真实验,以验证实现的PSF估计方法。基于仿真实验,在下一节中,我们提出了一种使自动PSF估计成为可能的程序。首先将实际文档图像作为示例来说明该过程,然后用估计的PSF和Lucy-Richardson Deconvolution方法进行恢复,并且将比较Deconvolution之前和之后的OCR精度。最后,我们将本文与未来工作的展望结束。

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