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A denoising approach to multisensor signal estimation
IEEE Transactions on Signal Processing, 2000Multisensor array processing of noisy measurements has received considerable attention in many areas of signal processing. The optimal processing techniques developed so far usually assume that the signal and noise processes are at least wide sense stationary, yet a need exists for efficient, effective methods for processing nonstationary signals ...
Anil M. Rao, Douglas L. Jones
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Rearranged nonlocal filters for signal denoising
Mathematics and Computers in Simulation, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gonzalo Galiano Casas +1 more
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Local means denoising of ECG signal
Biomedical Signal Processing and Control, 2019Abstract Electrocardiograph (ECG) signals denoising by Non-Local Means (NLM) method can achieve high signal-to-noise ratio improvements with less waveform distortion. But, computational complexity constraints its potential application in ECG signal real-time denoising.
Chunqiang Qian, Honghong Su, Helong Yu
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A denoising approach to multichannel signal estimation
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999Multichannel sensor array processing has received considerable attention in many important areas of signal processing. Almost all data recorded by multisensor instruments contain various amounts of noise, and much work has been done in developing optimal processing structures for estimating the signal source from the noisy multichannel observations ...
Anil M. Rao, Douglas L. Jones
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ICA based ECG signal denoising
2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013Significant diagnostic information in healthcare is obtained from Electrocardiogram (ECG) signals, so improvements in their analysis are also of growing importance. In the field of signal processing, the rapidly developing signal technology and flourishing variety of algorithms have proved successful targets for research in healthcare.
Mrinal Phegade, Prachi Mukherji
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Image Denoising for Signal-Dependent Noise
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006In this paper, we present a method for removing noise from digital images corrupted with additive, multiplicative, and mixed noise. An image patch from an ideal image is modeled as a linear combination of image patches from the noisy image. We propose to fit this image model to the real-world image data in the total least square (TLS) sense, because ...
Keigo Hirakawa, Thomas W. Parks
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Trimmed thresholding with SURE for denoising signals
2012 IEEE 55th International Midwest Symposium on Circuits and Systems (MWSCAS), 2012We propose a signal denoising method based on the undecimated wavelet transform. The proposed method uses the well-known Stein`s Unbiased Risk Estimator (SURE). A derivation of SURE with trimmed thresholding of the undecimated wavelet transform coefficients is given and an adapted algorithm is developed to solve the resulting minimax problem.
Maha A. Hassanein +3 more
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Comparison of the Wavelet Denoising Methods for Denoising of Phonocardiogram Signal
2021Heart diseases are the number one cause of death all over the world. Many deaths are caused due to late detection of heart diseases. During the process of heart sound recording, beside heart sound, environment noise is being recorded too. In this work signal denoising was performed using wavelet denoising method.
Dželila Mehanović +3 more
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A novel denoising method for acoustic signal
2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2017A novel denoising method which introduces guided filter form image processing filed to denoise acoustic signal is proposed in this paper. It is important to choose a right guidance signal for the guided filter and wavelet denoising will be used to get guidance signal in this paper.
Qiuju Li +3 more
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Leveraging end-to-end denoisers for denoising periodic signals
2021 29th European Signal Processing Conference (EUSIPCO), 2021Jules Rio +3 more
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