复小波变换
第二代小波变换
谐波小波变换
平稳小波变换
小波变换
小波
小波包分解
离散小波变换
计算机科学
吊装方案
连续小波变换
树(集合论)
人工智能
算法
模式识别(心理学)
数学
数学分析
作者
Ivan Selesnick,Richard G. Baraniuk,NG Kingsbury
出处
期刊:IEEE Signal Processing Magazine
[Institute of Electrical and Electronics Engineers]
日期:2005-11-01
卷期号:22 (6): 123-151
被引量:2379
标识
DOI:10.1109/msp.2005.1550194
摘要
The paper discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing. The authors use the complex number symbol C in CWT to avoid confusion with the often-used acronym CWT for the (different) continuous wavelet transform. The four fundamentals, intertwined shortcomings of wavelet transform and some solutions are also discussed. Several methods for filter design are described for dual-tree CWT that demonstrates with relatively short filters, an effective invertible approximately analytic wavelet transform can indeed be implemented using the dual-tree approach.
科研通智能强力驱动
Strongly Powered by AbleSci AI