1. Department of Automation, North China Electric Power University, Baoding, Hebei 071003, China
2. Department of Mathematics and Physics, North China Electric Power University, Baoding, Hebei 071003, China
Abstract:The image reconstruction algorithm of electrical capacitance tomography (ECT) based on deep wavelet network is presented . The Landweber algorithm is used to generate the initial reconstructed image as the input of the network. Taking the U-Net deep convolutional neural network model as the backbone model, the wavelet transform is introduced into the upper and lower sampling layers to extract the features of different levels and the high-frequency feature transfer channel is built through a skip connection to retain more detailed information and make full use of global and local information features in the feature map. Both simulation and experimental results show that the proposed image reconstruction algorithm has higher image reconstruction accuracy. The average relative image errors of simulated and static experimental reconstructed images were 0.1918 and 0.6570, respectively, with average correlation coefficients of 0.9685 and 0.8169.
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