A Novel 9/7 Wavelet Filter banks For Texture Image Coding

This paper proposes a novel 9/7 wavelet filter bank for texture image coding applications based on lifting a 5/3 filter to a 7/5 filter, and then to a 9/7 filter. Moreover, a one-dimensional optimization problem for the above 9/7 filter family is carried out according to the perfect reconstruction (PR) condition of wavelet transforms and wavelet properties. Finally, the optimal control parameter of the 9/7 filter family for image coding applications is determined by statistical analysis of compressibility tests applied on all the images in the Brodatz standard texture image database. Thus, a new 9/7 filter with only rational coefficients is determined. Compared to the design method of Cohen, Daubechies, and Feauveau, the design approach proposed in this paper is simpler and easier to implement. The experimental results show that the overall coding performances of the new 9/7 filter are superior to those of the CDF 9/7 filter banks in the JPEG2000 standard, with a maximum increase of 0.185315 dB at compression ratio 32:1. Therefore, this new 9/7 filter bank can be applied in image coding for texture images as the transform coding kernel.

[1]  Benjamin Belzer,et al.  Wavelet filter evaluation for image compression , 1995, IEEE Trans. Image Process..

[2]  L. Villemoes Energy moments in time and frequency for two-scale difference equation solutions and wavelets , 1992 .

[3]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[4]  Nanning Zheng,et al.  Optimization Design of Biorthogonal Wavelets for Embedded Image Coding , 2007, IEICE Trans. Inf. Syst..

[5]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[6]  GUOAN YANG,et al.  An Optimization Algorithm for Biorthogonal Wavelet Filter Banks Design , 2008, Int. J. Wavelets Multiresolution Inf. Process..

[7]  Dong Wei,et al.  A new class of biorthogonal wavelet systems for image transform coding , 1998, IEEE Trans. Image Process..

[8]  I. Daubechies,et al.  A STABILITY CRITERION FOR BIORTHOGONAL WAVELET BASES AND THEIR RELATED SUBBAND CODING SCHEME , 1992 .

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

[10]  Nanning Zheng,et al.  Optimal wavelet filter design for remote sensing image compression , 2007 .

[11]  P. P. Vaidyanathan,et al.  A new class of two-channel biorthogonal filter banks and wavelet bases , 1995, IEEE Trans. Signal Process..

[12]  Yo-Sung Ho,et al.  Efficient Wavelet Lifting Scheme Based on Filter Optimization and Median Operator , 2009, 2009 IEEE-RIVF International Conference on Computing and Communication Technologies.

[13]  Thierry Blu,et al.  Mathematical properties of the JPEG2000 wavelet filters , 2003, IEEE Trans. Image Process..

[14]  David S. Taubman,et al.  High performance scalable image compression with EBCOT , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[15]  Benjamin W. Wah,et al.  Optimization Design of Biorthogonal Filter Banks for Image Compressing , 2001, 2008 International Symposium on Information Science and Engineering.

[16]  L. Cheng,et al.  Popular biorthogonal wavelet filters via a lifting scheme and its application in image compression , 2003 .

[17]  Martin Vetterli,et al.  Wavelets and filter banks: theory and design , 1992, IEEE Trans. Signal Process..

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

[19]  Wim Sweldens,et al.  The lifting scheme: a construction of second generation wavelets , 1998 .

[20]  I. Daubechies,et al.  Factoring wavelet transforms into lifting steps , 1998 .

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