Erratic noise suppression using iterative structure‐oriented space‐varying median filtering with sparsity constraint

Singular value decomposition (SVD) is a coherency-based technique that provides both signal enhancement and noise suppression. It has been implemented in a variety of seismic applications — mostly on a global scale. In this paper, we use SVD to improve the signal-to-noise ratio of unstacked and stacked seismic sections, but apply it locally to cope with coherent events that vary with both time and offset. The local SVD technique is compared with [Formula: see text] deconvolution and median filtering on a set of synthetic and real-data sections. Local SVD is better than [Formula: see text] deconvolution and median filtering in removing background noise, but it performs less well in enhancing weak events or events with conflicting dips. Combining [Formula: see text] deconvolution or median filtering with local SVD overcomes the main weaknesses associated with each individual method and leads to the best results.

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Impulse Noise Suppression Method by Median Filtering with Parity Extraction

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.846-847.991 ◽

2013 ◽

Vol 846-847 ◽

pp. 991-994

Author(s):

Zhen Xing Li

Keyword(s):

Impulse Noise ◽

Noise Suppression ◽

Median Filter ◽

Window Size ◽

New Method ◽

Median Filtering ◽

Experiment Data ◽

Simulation And Experiment ◽

Suppression Method

A new impulse noise suppression method by median filtering with parity extraction was proposed in this paper. The window size of the median filter has important effect on the performance of the filtering result, larger window size can suppress impulse noise effectively but often at cost of loss of the detail information of the signal, while smaller window size can protect the detail information better but results in degrading of the noise suppression. Parity extraction is done to the signal at first and median filtering carries on the odd and even part respectively, and then a new method of median filtering with short window size to suppress the impulse noise is obtained. Simulation and experiment data of telemetry process results show the effectiveness of the proposed method.

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Impulse Noise Suppression Method for Telemetry Signal by Multi-Scale Median Filtering

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.989-994.3726 ◽

2014 ◽

Vol 989-994 ◽

pp. 3726-3729

Author(s):

Xiu Fang Liu

Keyword(s):

Wavelet Transform ◽

Wavelet Decomposition ◽

Impulse Noise ◽

Noise Suppression ◽

Window Size ◽

Frequency Domain Analysis ◽

Median Filtering ◽

Multi Scale ◽

Filtering Technique ◽

Suppression Method

The telemetry signal is often interfered with impulse noise, which results in difficulty in time domain and frequency domain analysis results. Hereby a new impulse noise suppression method based on wavelet transform and median filtering technique was proposed. The received signal is decomposed into detailed components and approximate components, and then the median filtering is carried on the wavelet decomposition components with vary filtering window size according to the wavelet transform scale respectively. This method can suppress the impulse noise effectively and keep the detail information of the signal from the loss at the same time. The simulation and experimental results prove the effectiveness of the method.

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Comparison of the Normal and Noise-Suppression Settings on the Spectra 22 Speech Processor of the Nucleus TM 22-Channel Cochlear Implant System

American Journal of Audiology ◽

10.1044/1059-0889.0403.55 ◽

1995 ◽

Vol 4 (3) ◽

pp. 55-58 ◽

Cited By ~ 3

Author(s):

Laura K. Holden ◽

Margaret W. Skinner ◽

Timothy A. Holden

Keyword(s):

Cochlear Implant ◽

Noise Suppression ◽

Speech Processor ◽

Implant System

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Endogenous Noise Suppression During Covert Orienting

PsycEXTRA Dataset ◽

10.1037/e501882009-598 ◽

2000 ◽

Author(s):

Edward Awh ◽

John Serences ◽

Kelsey Libner ◽

Michi Matsukura

Keyword(s):

Noise Suppression ◽

Covert Orienting

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The use of a combined reseiver as a hydrophone to increase noise suppression

Izmeritel`naya Tekhnika ◽

10.32446/0368-1025it.2019-5-61-64 ◽

2019 ◽

pp. 61-64

Author(s):

V. V. Petrov

Keyword(s):

Noise Suppression

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An Absolute Phase Estimation Method for Interferometry Imagery

Journal of Engineering Technology and Applied Physics ◽

10.33093/jetap.2019.1.2.4 ◽

2019 ◽

Vol 1 (2) ◽

pp. 14-19

Author(s):

Sui Ping Lee ◽

Yee Kit Chan ◽

Tien Sze Lim

Keyword(s):

Noise Suppression ◽

Estimation Method ◽

Phase Image ◽

Phase Estimation ◽

Phase Reconstruction ◽

Estimation Algorithms ◽

Absolute Phase ◽

Filtering Rate ◽

Interferometric Phase ◽

Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

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