Smooth biorthogonal wavelets for applications in image compression

We introduce a new family of smooth, symmetric biorthogonal wavelet basis. The new wavelets are a generalization of the Cohen, Daubechies and Feauveau (CDF) biorthogonal wavelet systems proposed in 1992. Smoothness is controlled independently in the analysis and synthesis bank and is achieved by optimization of the discrete finite variation (DFV) measure introduced for orthogonal wavelet design. The DFV measure dispenses with a measure of differentiability (for smoothness) which requires-a large number of vanishing wavelet moments (e.g., Holder and Sobolev exponents) in favor of a smoothness measure that uses the fact that only a finite depth of the filter bank tree is involved in most practical applications. Image compression examples applying the new filters using the embedded wavelet zerotree (EZW) compression algorithm due to Shapiro (1993) shows that the new basis functions performs better when compared to the classical CDF 7/9 wavelet basis.

[1]  Michel Barlaud,et al.  Image coding using wavelet transform , 1992, IEEE Trans. Image Process..

[2]  Jan E. Odegard,et al.  Discrete finite variation: a new measure of smoothness for the design of wavelet basis , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[3]  I. Daubechies,et al.  Biorthogonal bases of compactly supported wavelets , 1992 .

[4]  Michael Unser Approximation power of biorthogonal wavelet expansions , 1996, IEEE Trans. Signal Process..

[5]  Peter N. Heller,et al.  The design of maximally smooth wavelets , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[6]  Peter N. Heller,et al.  Regular M-band wavelets and applications , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  Peter N. Heller,et al.  Optimally smooth symmetric quadrature mirror filters for image coding , 1995, Defense, Security, and Sensing.

[8]  Jan Erik Odegard Moments, smoothness and optimization of wavelet systems , 1996 .

[9]  Mohammed Ghanbari,et al.  On the performance of linear phase wavelet transforms in low bit-rate image coding , 1996, IEEE Trans. Image Process..

[10]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[11]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..