Blind deconvolution of blurred images from multiple observations using the GCD algorithm

M. Hadhoud, M. Dessouky, F. El-Samie, S. El-Khamy
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Abstract

This paper suggests an approach for the 2-D blind deconvolution of more than two observations using the two-dimension greatest common divisor (GCD) algorithm. This approach benefits from the information in each observation at the same time instead of using only two observations at a time. The approach depends on forming a combinational image from the available observations and performing the 2-D GCD on this image with all observations and then averaging the results to obtain the estimated image. Results are presented to illustrate the superiority of the proposed method.
使用GCD算法对多个观测值的模糊图像进行盲反卷积
本文提出了一种利用二维最大公约数(GCD)算法对两个以上观测值进行二维盲反卷积的方法。这种方法的优点是同时利用每个观测值中的信息,而不是一次只使用两个观测值。该方法依赖于从可用的观测数据中形成一个组合图像,并对所有观测数据对该图像进行二维GCD,然后对结果进行平均以获得估计图像。实验结果表明了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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