图像的神经并发子采样和插值

Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030) Pub Date : 1999-10-28 DOI:10.1109/TENCON.1999.818674

Jong-Ok Kim, Byung-Tae Choi, A. Morales, S. Ko

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引用次数: 4

摘要

提出了一种基于前馈神经网络(FNN)的图像子采样和插值新方法。该方法采用具有三个隐层的单个FNN进行子采样和插值，具有速度快、并行处理能力强、图像再现质量好等优点。实验结果表明，该方法比传统方法具有更高的性能。

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Neural concurrent subsampling and interpolation for images

This paper presents a new method for image subsampling and interpolation based on the feedforward neural network (FNN). The proposed technique employs a single FNN with three hidden layers for both subsampling and interpolation, providing the advantages of high speed, parallel processing capability, and good image reproduction quality. Experimental results show that the proposed technique exhibits an increased performance over conventional ones.

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来源期刊

Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030)

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