Context based multiwavelet image coding using SPIHT framework
Machine Graphics & Vision International Journal
A New Multiwavelet-Based Approach to Image Fusion
Journal of Mathematical Imaging and Vision
A multivariate thresholding technique for image denoising using multiwavelets
EURASIP Journal on Applied Signal Processing
Efficient transmission of vector data over the Internet
International Journal of Geographical Information Science
Face recognition based on multi-scale singular value features
WSEAS Transactions on Computers
Approach of medicial image fusion based on multiwavelet transform
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
The performance of multiwavelets based OFDM system under different channel conditions
Digital Signal Processing
A novel image compression method using watermarking technique in JPEG coding process
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
A hierarchical Bayesian model for frame representation
IEEE Transactions on Signal Processing
A Radon-Multiwavelet Based OFDM System Design and Simulation Under Different Channel Conditions
Wireless Personal Communications: An International Journal
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Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of the desirable properties. The relatively new field of multiwavelets shows promise in obviating some of the limitations of wavelets. Multiwavelets offer more design options and are able to combine several desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This paper presents new multiwavelet transform and quantization methods and introduces multiwavelet packets. Extensive experimental results demonstrate that our techniques exhibit performance equal to, or in several cases superior to, the current wavelet filters