Title :
Seismic signal denoising method based on curvelet transform
Author :
Aidi Wu ; Xiuling Zhao
Author_Institution :
Dept. of Math. & Inf. Sci., Tianjin Univ. of Technol. & Educ., Tianjin, China
Abstract :
Considering the characteristic of curvelet coefficients in difference levels, a adaptive threshold denoising method is proposed by using fast discrete curvelet transform. Using total variation minimization reduces the noise while edges are preserved. Experiment results show that the method proposed is more effective than the traditional wavelet denoising method.
Keywords :
discrete wavelet transforms; geophysical signal processing; seismic waves; signal denoising; adaptive threshold denoising method; curvelet coefficients; difference levels; discrete curvelet transforms; seismic signal denoising; total variation minimization; wavelet denoising; Image edge detection; Noise reduction; Signal to noise ratio; TV; Wavelet transforms; curvelet transform; seismic signal; signal denoising; total variation;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584236