计算机工程与应用 ›› 2016, Vol. 52 ›› Issue (18): 199-202.

• 图形图像处理 • 上一篇    下一篇

基于三维曲波变换的弱信号恢复方法研究

胡  雨1,谢  凯1,阮宁君1,伍  鹏2,3,贺建飚4,刘从浩1   

  1. 1.长江大学 电子信息学院 油气信息处理与识别研究所,湖北 荆州 434023
    2.中国地质大学 信息工程学院,武汉 430074
    3.国家地理信息系统工程技术研究中心,武汉 430074
    4.中南大学 信息科学与工程学院,长沙 410083
  • 出版日期:2016-09-15 发布日期:2016-09-14

Method of weak signal recovery based on 3D-curvelet transform

HU Yu1, XIE Kai1, RUAN Ningjun1, WU Peng2,3, HE Jianbiao4, LIU Conghao1   

  1. 1.Institute for Oil & Gas Information Processing and Identification, Electronics & Information College, Yangtze University, Jingzhou, Hubei 434023, China
    2.College of Information Engineering, China University of Geosciences, Wuhan 430074, China
    3.National Engineering Research Center for Geographic Information System, Wuhan 430074, China
    4.School of Information Science and Engineering, Central South University, Changsha 410083, China
  • Online:2016-09-15 Published:2016-09-14

摘要: 传统的弱信号恢复方法在强噪声背景下具有较大的局限性,有用的信息往往淹没在强噪声背景下不易被识别。针对这个难点,提出一种基于三维曲波变换的弱信号恢复的方法。该方法将三维曲波变换和自适应滤波器相融合,从而提高数据中弱信号的能量,使得弱信号更易于被恢复。为了验证该方法的有效性,对楔形模型与实际三维数据进行处理。实验结果表明,恢复后的数据信噪比提高了2 dB到3 dB,频带也被拓宽了150 Hz,弱信号得到较好的恢复。

关键词: 弱信号恢复, 三维曲波变换, 信噪比, 自适应最优阈值, 自适应滤波器

Abstract: Conventional methods of weak signal recovery are limited under strong noise condition. Useful information is often submerged in heavy noise, which is not easy to identify. As to this problem, a weak signal recovery method based on 3D-curvelet transform is proposed in this paper. Combining 3D-curvelet transform with the adaptive filter is to recover weak signal. Model of wedge and actual data are processed by this method. The experimental results show that the signal to noise ratio of data improves 2 dB to 3 dB and the frequency is increased 150 Hz. Obviously, the weak signal is recovered.

Key words: recovery of weak signal, 3D-curvelet transform, signal to noise ratio, adaptive optimal threshold, adaptive filter