Doppler Signal Denoising Based on Feature Adaptive Wavelet Shrinkage Method

Zhao Yin; Jing Jin; Yan Wang; Yi Shen

doi:10.4028/www.scientific.net/AMR.532-533.702

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 532-533Doppler Signal Denoising Based on Feature Adaptive...

Doppler Signal Denoising Based on Feature Adaptive Wavelet Shrinkage Method

Abstract:

The envelope extraction of Doppler signal spectrum is very important in ultrasonic blood flow detection, due to the fact that it can provide the diagnosis information of blood circulatory system. Doppler signals are often polluted by noises, which will affect the performance of the envelope extraction. Therefore, it is necessary to remove the noises before extracting the spectrum envelope. In this paper, a Doppler denoising method based on the Feature Adaptive Wavelet Shrinkage is proposed. The advantage of this method is that the threshold of each coefficient is set by using the coefficient at the current location and its two neighbor coefficients. Simulation results demonstrate that the proposed method can remove the noises of Doppler signals more effectively compared to the traditional wavelet threshold method.

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Periodical:

Advanced Materials Research (Volumes 532-533)

Pages:

702-707

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.532-533.702

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Online since:

June 2012

Authors:

Zhao Yin, Jing Jin, Yan Wang, Yi Shen

Keywords:

De-Noising, Doppler Spectrum, Feature Adaptive Wavelet Shrinkage, Wavelet Threshold

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References

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