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    Please use this identifier to cite or link to this item: http://140.128.103.80:8080/handle/310901/21477


    Title: Wavelet-based image interpolation using multilayer perceptrons
    Authors: Huang, Y.-L.
    Contributors: Department of Computer Science, Tunghai University
    Keywords: Image resampling;Interpolation;Neural network;Subband filtering;Wavelet transform
    Date: 2005
    Issue Date: 2013-05-14T09:07:15Z (UTC)
    Abstract: Changing the resolution of digital images and video is needed image processing systems. In this paper, we present nonlinear interpolation schemes for still image resolution enhancement. The proposed neural network interpolation method is based on wavelet reconstruction. With the wavelet decomposition, the image signals can be divided into several time-frequency portions. In this work, the wavelet decomposition signal is used to train the neural networks. The pixels in the low-resolution image are used as the input signal of the neural network to estimate all the wavelet sub-images of the corresponding high-resolution image. The image of increased resolution is finally produced by the synthesis procedure of wavelet transform. In the simulation, the proposed method obtains much better performance than other traditional methods. Moreover, the easy implementation and high flexibility of the proposed algorithm also make it applicable to various other related problems. ? Springer-Verlag London Limited 2004.
    Relation: Neural Computing and Applications
    Volume 14, Issue 1, March 2005, Pages 1-10
    Appears in Collections:[資訊工程學系所] 期刊論文

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