Semi-blind defocused image restoration with neural network and wiener filtering;
基于神经网络和维纳滤波的半盲离焦图像复原
A novel semi-blind defocused image restoration technique is proposed, which is based on dual-tree complex wavelet transform and wavelet neural network(WNN).
提出了一种基于二元树复小波变换和神经网络的半盲离焦图像复原算法,首先利用二元树复小波变换和特征值分解提取图像的特征矢量,将该矢量用来训练小波神经网络,利用训练好的网络估计离焦模糊参数。
A novel semi-blind defocused image restoration technique is proposed, which is based on back propagation(BP) neural network and inverse filtering.
本文利用BP神经网络和逆滤波器提出了一种新的半盲离焦图像复原算法。
A super-resolution blind restoration algorithm for defocus blurred images was suggested according to the model of optical defocusing by using autocorrelation of derivative image.
针对离焦模糊图像的盲复原算法的研究具有重要的实际意义和实用价值。
An algorithm to solve the blur problem of processed infrared defocused image based on the LIP model of Lee algorithm of image enhancement was presented.
针对红外离焦图像处理后图像模糊效应问题 ,提出一种基于 L IP模型的 L ee图像增强算法的去模糊图像的算法 ,它能够有效地处理图像增强后的模糊效应 ,实现图像的清晰成像 ,该算法便于实现 ,可广泛地应用于图像显示技术 。
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