Contrast enhancement in emission tomography by way of synergistic PET/CT image combination
Computer Methods and Programs in Biomedicine
Multifocus image fusion using the nonsubsampled contourlet transform
Signal Processing
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Biological image fusion using a NSCT based variable-weight method
Information Fusion
Original article: Optimal quality for image fusion with interpolatory parametric filters
Mathematics and Computers in Simulation
A robust content based audio watermarking using UDWT and invariant histogram
Multimedia Tools and Applications
Comparative study of different wavelets for hydrologic forecasting
Computers & Geosciences
Wavelet transform based consonant - vowel (CV) classification using support vector machines
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Computation of wavelet coefficients from average samples
Journal of Computational and Applied Mathematics
Seismic noise study for accurate P-wave arrival detection via MODWT
Computers & Geosciences
Medical image denoising using adaptive fusion of curvelet transform and total variation
Computers and Electrical Engineering
Hi-index | 35.69 |
Two separately motivated implementations of the wavelet transform are brought together. It is observed that these algorithms are both special cases of a single filter bank structure, the discrete wavelet transform, the behavior of which is governed by the choice of filters. In fact, the a trous algorithm is more properly viewed as a nonorthonormal multiresolution algorithm for which the discrete wavelet transform is exact. Moreover, it is shown that the commonly used Lagrange a trous filters are in one-to-one correspondence with the convolutional squares of the Daubechies filters for orthonormal wavelets of compact support. A systematic framework for the discrete wavelet transform is provided, and conditions are derived under which it computes the continuous wavelet transform exactly. Suitable filter constraints for finite energy and boundedness of the discrete transform are also derived. Relevant signal processing parameters are examined, and it is observed that orthonormality is balanced by restrictions on resolution