摘要
本文介绍了小波变换理论 ,讨论了基本小波函数的选取准则和小波变换算法 ,分析了小波变换与人工智能等其它方法的结合方式和特点 .通过介绍小波变换在信号瞬态分析、图像边沿检测、图像去噪、模式识别、数据压缩、分形信号分析等方面的应用实例 ,讨论了小波变换在处理非平稳信号和复杂图像时的优势 .最后 ,对小波变换理论的发展及其应用前景作了描述 .
This paper, the wavelet transform theory is introduced, the criterions of choosing basic wavelet function and the algorithm of wavelet transform are discussed, and the ways and characteristics of wavelet transform combining with artificial intelligence and other methods are analyzed. The application examples of wavelet transform in the fields of signal instantaneous analysis, image edge detection, image denoising, pattern recognition, data compression and fractal signal analysis are reviewed. The advantage of processing unstable signals and complicated images by wavelet transform is discussed. At the end, the development and future trends of wavelet transform are pointed out.
出处
《信息与控制》
CSCD
北大核心
2004年第1期67-71,共5页
Information and Control
基金
辽宁省自然科学基金资助项目 ( 0 10 70 5 )
