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本文用人工神经网络实现极大熵约束下的图像重建,并提出综合图像恢复法,对从脉冲性噪声中恢复图像有较好结果。本文还用扩展的自相关函数(EAC)法改进普通的LPC自相关函数法恢复图像也有较好的结果。以上两种图像恢复领域中新方法对解决损失部份信息下的图像重建有一定意义。
In this paper, artificial neural network (ANN) is used to reconstruct the image under the constraint of maximum entropy, and a comprehensive image restoration method is proposed, which has good results on recovering the image from impulsive noise. In this paper, we also use the extended autocorrelation function (EAC) method to improve the ordinary LPC autocorrelation function to recover the image and have better results. The above two methods in the field of image restoration have some significance to solve the image reconstruction under the loss of some information.