Extraction of subimages by lifting wavelet filters

This paper proposes a method for extracting subimages from a huge reference image by learning lifting wavelet filters. Lifting wavelet filters are biorthogonal wavelet filters containing free parameters developed by Sweldens. Our method is to learn such free parameters using some training subimages so as to vanish their high frequency components in the yand xdirections. The learnt wavelet filters have the feature of training subimages. Applying such wavelet filters to the reference image, we can detect the locations where the high frequency components are almost the same as those of the target subimage. key words: extraction, subimage, learning, lifting wavelet lter

[1]  K. Niijima,et al.  Design of optimal lifting wavelet filters for data compression , 1998, Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380).

[2]  葛目 幸一 Design theory of wavelets with free parameters , 1999 .

[3]  Koichi Niijima,et al.  Sub-image extraction by learnt lifting wavelet filters , 1999, ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359).

[4]  David Salesin,et al.  Wavelets for computer graphics: a primer. 2 , 1995, IEEE Computer Graphics and Applications.

[5]  W. Sweldens The Lifting Scheme: A Custom - Design Construction of Biorthogonal Wavelets "Industrial Mathematics , 1996 .

[6]  P. P. Vaidyanathan,et al.  Theory and design of optimum FIR compaction filters , 1998, IEEE Trans. Signal Process..

[7]  K. Niijima,et al.  Optimization of lifting wavelet filters for ECG data compression , 1998, ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344).

[8]  Koichi Kuzume,et al.  Wavelets with convolution-type orthogonality conditions , 1999, IEEE Trans. Signal Process..