基于“图像”分割的小波脊线提取算法

J4 ›› 2012, Vol. 29 ›› Issue (6): 665-670.

基于“图像”分割的小波脊线提取算法

陈蕴谷,苏本跃

安庆师范学院计算机与信息学院, 安徽安庆 246011

收稿日期:2011-10-14 修回日期:2011-11-30 出版日期:2012-11-28 发布日期:2014-03-20
通讯作者: 陈蕴谷 (1984-) 安徽太湖人，硕士，助教，从事图像处理、信号分析的教学与研究。 E-mail:chygu2008@126.com
基金资助:
国家自然科学基金（60862003）、科技部国际合作项目（2009DFR10530）、安庆师范学院校青年基金

Ridge extraction based on “image” segmentation

Chen Yungu, Su Benyue

School of Computer & Information, Anqing Teachers College, Anqing 246011, China

Received:2011-10-14 Revised:2011-11-30 Published:2012-11-28 Online:2014-03-20

摘要/Abstract

摘要：

针对传统脊线提取算法不能同时兼顾速度和精度的问题，本文提出了一种新的基于“图像”分割的小波脊线提取算法。对渐近性信号进行连续小波变换以后，模值较大的小波系数往往集中在时间-尺度平面上几个分散的区域，将小波系数模值矩阵看作一个“图像”，对其分割，再对分割得到的每个区域确定其极值位置可得到小波脊线。仿真实验表明：本文算法不仅较传统脊线算法在精度和效率都有所提高，在信号去噪和信号分离中也表现良好。

关键词: 图像与信息处理, 图像分割, 脊提取, 信号去噪, 信号分离

Abstract:

Aimed at the problem of not taking into account both precision and efficiency, a novel ridges extraction algorithm based on “image” segmentation is proposed. For an asymptotic signal, its continuous wavelet coefficients with large absolute values usually distribute in some dispersed regions in the time-scale plane, take the absolute wavelet coefficients matrix as an “image”, the wa velet ridge can be detected by segmenting the “image” and locating the maximum value from each region. Experimental results show that the proposed algorithm not only outperforms general algorithms with respect to precision and efficiency, but also works well in signal denoising and signal separation.

Key words: image and information processing, image segmentation, ridge extraction, signal separation

中图分类号:

TP391.41

陈蕴谷,苏本跃. 基于“图像”分割的小波脊线提取算法[J]. J4, 2012, 29(6): 665-670.

Chen Yungu, Su Benyue. Ridge extraction based on “image” segmentation[J]. J4, 2012, 29(6): 665-670.

参考文献

[1] Delprat N, Escudie B, et al., Asymptotic wavelet and Gabor analysis: extraction of instantaneous frequencies [J], IEEE Transactions on Information Theory, 1992, 38(2): 644-664.
[2] Carmona R, Hwang W L, Torresani B, Characterization of signals by the ridges of their wavelet transforms [J], IEEE Transactions on Signal Processing, 1997,45(10): 2586-2590.
[3] Carmona R, Hwang W L, Torresani B, Multi-ridge detection and time-frequency reconstruction [J], IEEE Transactions on Signal Processing, 1999,47(2): 480-492.
[4] Helene L, Catherine M, Ridge extraction from the scalogram of the uterine electromyogram [C] Proceedings of the IEEE-SP International Symposium．Pittsburgh，1998：245-248.
[5] Liebling M, Bernhard TF, et al., Continuous wavelet transform ridge extraction for spectral interferometry imaging [C], Proceedings of the SPIE Conference on Coherence Domain Optical Methods and Optical Coherence Tomography in Biomedicine IX, San José CA, USA, 2005 ,5690:397-402.
[6] Zhang Xiaodong, Signal Representation and Reconstruction Based on Ridge Extraction [D],Southeasr University ,2003(in Chinese) 张晓冬, 基于脊提取的信号表示和重建 [D],南京：东南大学博士学位论文，2003.
[7] Liu Benyong, An Introduction To Nonstationary Signal Analysis[M],Beijing: National Defence Industry Press,2006(in Chinese) 刘本永, 非平稳信号分析导论[M]. 北京:国防工业出版社，2006.
[8] M. J. Shensa, Discrete inverses for non-orthogonal wavelet transforms [J]. IEEE Transactions on Signal Processing 1996, 44(4): 798–807.
[9] Qin Yi, Research on Wavelet Theory for Signal Analysis and Integrated Wavelet Analyzer[D].Chongqing University,2008(in Chinese) 秦毅,信号小波理论与一体化小波分析仪的研究 [D]. 重庆：重庆大学博士学位论文，2008.
[10] Zheng Shenghua, XU Dazhuan, Detection of LFM signals based on wavelet ridge extracting and Hough transform[J]. (量子电子学报),Chinese Journal of Quantum Electronics, 2008,25(2):145-150. 郑生华,徐大专,基于小波脊线-Hough变换的LFM信号检测[J]. 量子电子学报, 2008, 25(2):145-150.
[11] L Jing, Ridge reconstruction based on inverse wavelet transform [J]. Journal of Sound and Vibration, 2006, 294 (4-5) : 916-926.