Highly scalable image coding for multimedia applications
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Rotation and scale invariant wavelet feature for content-based texture image retrieval
Journal of the American Society for Information Science and Technology
Log-Polar Wavelet Energy Signatures for Rotation and Scale Invariant Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotation-invariant texture feature for image retrieval
Computer Vision and Image Understanding
Extraction of Shift Invariant Wavelet Features for Classification of Images with Different Sizes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Persian/arabic handwritten word recognition using M-band packet wavelet transform
Image and Vision Computing
WAMUS'05 Proceedings of the 5th WSEAS International Conference on Wavelet Analysis and Multirate Systems
Non-Iterative Hierarchical Registration for Medical Images
Journal of Signal Processing Systems
On bounds of shift variance in two-channel multirate filter banks
IEEE Transactions on Signal Processing
An algorithm for real-time noise cancellation in wireless sensor networks
WTS'10 Proceedings of the 9th conference on Wireless telecommunications symposium
Seismic noise study for accurate P-wave arrival detection via MODWT
Computers & Geosciences
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We address the time-varying problem of wavelet transforms, and a new translation-invariant wavelet representation algorithm is proposed. Using the algorithm introduced by Beylkin (see SIAM J. Numer. Anal., vol. 29, p.1716-1740, 1992), we compute the wavelet transform for all the circular time shifts of a length-N signal in O(N log N) operations. The wavelet coefficients of the time shift with minimal cost are selected as the best representation of the signal using a binary tree search algorithm with an appropriate cost function. We apply the translation-invariant representation algorithm to a geoacoustic data compression application. The results show that the new algorithm can reduce the distortion (the squared error in our case) substantially, if the input signals are transients that are sensitive to time shifts