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Journal of Flow Visualization and Image Processing

ISSN for PRINT: 1065-3090

Institutional price:	$586.00
Issues per year:	4

Best Paper Award Selection - Editorial Board Site

2002, Volume9

96 pages

Issue price - $140.00

ANALYSIS OF SYMMETRIC MULTIWAVELETS AND ITS APPLICATION FOR IMAGE COMPRESSION

Chen Jiazhong
National Storage System Laboratory, Department of Computer Science and Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, P. R. China

Zhou Jingli
National Storage System Laboratory, Department of Computer Science and Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, P. R. China

Yu Shengsheng
National Storage System Laboratory, Department of Computer Science and Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, P. R. China

He Xiaocheng
National Storage System Laboratory, Department of Computer Science and Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, P. R. China

Li Jun
National Storage System Laboratory, Department of Computer Science and Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, P. R. China

ABSTRACT

Multiwavelets are the new addition to the body of wavelet theory. It is also based on the idea of multiresolution analysis (MRA). An MRA is usually generated by one scaling function. However, such wavelets cannot possess the properties of compact support, linear phase, and orthogonality simultaneously. Realized as matrix-valued filterbanks leading to wavelet bases, multiwavelets can offer these three properties simultaneously which are strongly desired in many applications, such as a fast multiresolution pyramid decomposition algorithm of image with the 2 ґ 2 matrix. To succeed using the EZW algorithms, we wish there still are some of the relationships between ancestors and their offspring. But the relationship is not very clear after the conventional iteration of multiwavelet decomposition which is similar to the scalar wavelet decomposition, and the encoding effect and efficiency are not very good. Therefore, this paper presents full new decomposition and quantization methods adapt to the symmetric property of multiwavelets. Extensive experimental results demonstrate that our techniques exhibit performance equal or superior to the conventional decomposition methods.