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Alternative TitleImage super-resolution reconstruction method based on convolutional neural network
赵怀慈; 刘明第; 郝明国; 王立勇; 刘鹏飞; 赵洋
Rights Holder中国科学院沈阳自动化研究所
Patent Agent沈阳科苑专利商标代理有限公司 21002
Other AbstractThe invention relates to an image super-resolution reconstruction method based on a convolutional neural network, and the method comprises the steps: training an SRCNN convolutional neural network model through a data set, and obtaining the shallow texture feature information; establishing an eight-layer end-to-end neural network model based on feature transfer, and migrating shallow texture feature information to the first four layers of the neural network model to obtain model parameters of the first four layers; obtaining model parameters of four rear layers of the neural network model, andenhancing learnt characteristics; inputting image data to be reconstructed, and preprocessing the image data; obtaining a high-resolution image of the Y channel; and fusing the high-resolution imageof the Y channel, the image of the Cb channel and the image of the Cr channel to obtain a reconstructed image. According to the convolutional neural network model provided by the invention, a better super-resolution result is obtained, the subjective vision and objective evaluation indexes are obviously improved, the image definition and the edge sharpness are obviously improved, the convergence speed is higher, and the method has higher advantages in the aspect of fineness.
PCT Attributes
Application Date2017-12-25
Date Available2020-12-22
Application NumberCN201711417919.0
Open (Notice) NumberCN109961396A
Contribution Rank1
Document Type专利
Recommended Citation
GB/T 7714
赵怀慈,刘明第,郝明国,等. 一种基于卷积神经网络的图像超分辨率重建方法[P]. 2019-07-02.
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