Journal Article10.1007/S00521-004-0433-0
Wavelet-based image interpolation using multilayer perceptrons
TL;DR: The proposed neural network interpolation method is based on wavelet reconstruction, which obtains much better performance than other traditional methods and is applicable to various other related problems.
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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.
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Pann Ei San,Fengchun Tian,Zhiyong Shi,Minjun Deng +3 more
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David E. Rumelhart,James L. McClelland,Au +2 more
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TL;DR: The fundamental principles, basic mechanisms, and formal analyses involved in the development of parallel distributed processing (PDP) systems are presented in individual chapters contributed by leading experts.
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TL;DR: A scheme for image compression that takes into account psychovisual features both in the space and frequency domains is proposed and it is shown that the wavelet transform is particularly well adapted to progressive transmission.
Cubic convolution interpolation for digital image processing
TL;DR: It can be shown that the order of accuracy of the cubic convolution method is between that of linear interpolation and that of cubic splines.
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