采用卷积神经网络的小幅文本图像重聚焦算法

doi:10.3969/j.issn.1001-2400.2018.04.015

Abstract

Abstract:

We propose a new image refocusing algorithm based on the convolutional neural network. We analyze the traditional wiener filtering method, and derive it. We transform the frequency domain division into a cyclic convolution and decompose the kernel by SVD. After that, we design a new structure of the convolutional neural network by cyclic convolution and one-dimensional convolution. This network can not only simulate the defocusing process of wiener filtering, but also restore the image without a kernel, and have good anti-noise performance. At the same time, the convolutional neural network is fast-convergent and parameter insensitive.

Key words: defocusing blurring, Wiener filtering, convolutional neural network

WANG Kangkang;WANG Keyan;LI Yunsong. Text image refocusing by using the convolutional neural network[J].Journal of Xidian University, 2018, 45(4): 80-85.

References

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Text image refocusing by using the convolutional neural network

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