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Blurred Defocused Image Restoration Based on FRFT

机译:基于FRFT的模糊散焦图像恢复

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摘要

A technique for restoring the blurred image resulted from defocusing of the lens is proposed in this paper, which is based on fractional Fourier transform (FRFT).The FRFT, as a powerful tool for the analysis of time-varying signals, is closely connected with the optical imaging system. FRFT also can describe optical imaging process just like Fresnel diffractions, so a defocused imaging model based on FRFT is established to explain the blur phenomena of defocusing image. The defocused imaging model isgreatly different from the traditional point spread function (PSF) model, and enables to uncover the blur nature of non-focus image. Then, an image restoration method using the novel model is proposed to handle the blurred defocused image. The method adopted a new iterative phase retrieval approach which can approximately estimate phase signals from intensity signals of a single defocused image by means of FRFT. Restoring image may acquire sharp image by implementing inverse FRFT on complex image signal made from the estimated phase signals and intensity signals. Experimental results demonstrate that the method is effective in restoring blurred defocused image.
机译:本文提出了一种基于分数傅立叶变换(FRFT)的镜头散焦导致的模糊图像恢复技术.FRFT作为分析时变信号的有力工具,与光学成像系统。 FRFT也可以像菲涅耳衍射一样描述光学成像过程,因此建立了基于FRFT的散焦成像模型来解释散焦图像的模糊现象。散焦成像模型与传统的点扩散函数(PSF)模型有很大的不同,并且可以揭示非聚焦图像的模糊性质。然后,提出了一种使用新型模型的图像复原方法来处理模糊的散焦图像。该方法采用了一种新的迭代相位检索方法,该方法可以通过FRFT从单个散焦图像的强度信号中近似估计相位信号。通过对由估计的相位信号和强度信号构成的复杂图像信号实施逆FRFT,可以恢复清晰图像。实验结果表明,该方法可以有效地恢复模糊的散焦图像。

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