基于自适应K-SVD的能量泄漏恢复研究

doi:10.11720/wtyht.2020.1229

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Abstract

In view of the problem of residual signal (also known as energy leakage) in the noise profile of the existing conventional denoising method in the parameter selection,this paper proposes the energy leakage recovery method of adaptive K-SVD to achieve effective recycling of signals.Firstly,a high-quality sample is obtained by using traditional methods such as wavelet threshold and fx domain denoising to perform dictionary construction,and then the correlation coefficient matching criterion is introduced to sparsely decompose the residual profile so as to realize the secondary separation of random noise and residual effective signal.The experimental results show that the proposed algorithm can better balance the denoising and amplitude preservation of seismic signals and has adaptability.

Key words： energy leakage high-quality samples correlation coefficient matching criterion signal-to-noise separation

Received: 21 June 2019 Published: 22 April 2020

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	Articles by authors
	Zhen HE
	Si-Yuan CAO
	Hua-Jie HAO
	Xu-Yuan DUAN

	Yun-Pei ZHANG

Cite this article:

Zhen HE,Si-Yuan CAO,Hua-Jie HAO, et al. Research on energy leakage recovery of adaptive K-SVD[J]. Geophysical and Geochemical Exploration, 2020, 44(2): 362-371.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2020.1229 OR https://www.wutanyuhuatan.com/EN/Y2020/V44/I2/362

Algorithm flow chart

Wedge model test results
a—wedge model;b—noise wedge model;c—dictionary constructed under noise;d—noise dictionary denoising profile;e—noise dictionary denoising profile;f—noiseless dictionary denoising profile;g—noise dictionary denoising residuals;h—noiseless dictionary denoising residuals;i—wedge model 15^th signal;j—noise wedge model 15^th;k—noise dictionary denoising after 15^th;l—No15 after noiseless dictionary denoising

Tilt model section test results
a—tilt model;b—charging tilt model;c—wavelet threshold denoising profile;d—wavelet threshold denoising residual;e—effective signal for normal sample separation;f—effective signal for good sample separation;g—ordinary sample energy recovery results;h—high quality sample energy recovery results

Test results of the 75^th signal of tilt model
a—tilt model;b—tilt model noise;c—wavelet threshold denoising result;d—normal sample energy recovery result;e—good sample energy recovery result

Result of the practical test of the method
a—f-x domain denoising profile;b—f-x domain denoising residual;c—improved wavelet threshold denoising profile;d—improved wavelet threshold denoising residual;e—ASVD denoising proflie;f—ASVD denoising residual;g—f-x domain denoising energy recovery result(75^th channel);h—improved wavelet threshold denoising energy recovery result(75^th channel);i—ASVD denoising energy recovery result(75^th channel)

Actual data processing
a—2D actual data in a region;b—f-x domain denoising profile;c—f-x domain denoising residual;d—f-x domain denoising recovery profile;e—ASVD denoising proflie;f—ASVD denoising residual;g—ASVD domain denoising recovery profile

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