用神经网络恢复失焦图像

Hun-Chen Chen, J. Yen, Hung-Chun Chen
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引用次数: 5

摘要

失焦图像的复原是成像系统的重要组成部分。镜头离焦可能导致图像模糊。本文提出了一种基于神经网络的均匀失焦模糊模糊参数估计方法。利用圆霍夫变换在频域估计离焦图像的参数,并结合神经网络得到离焦图像的频响参数与均匀离焦模糊模型参数之间的关系。最后,利用空间连续点扩散函数(PSF)和训练好的神经网络对失焦图像进行复原。仿真结果表明,所提估计方法的平均误差小于0.48%,比现有方法的估计精度更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Restoration of out of focus images using neural network
Restoration of out of focus images is important role in imaging system. The lens defocus may cause image blurring. In this paper, a neural network approach to estimate the blur parameter for uniform out of focus blur is proposed. we estimate the parameter of defocused image in frequency domain by using circle Hough transform, and combine with neural network to have the relationship between the parameter of frequency response of out of focus image and the parameter of uniform out of focus blur model. Finally, we restore the out of focus image with its spatial continuous point spread function (PSF) and the trained neural network. The simulation result shows that the average error with the proposed estimation method is smaller than 0.48%, and more accurate than the existing methods.
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