Wiener filter ≈ Wiener filter
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Multichannel Audio Source Separation With Deep Neural Networks Open
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A generic EEG artifact removal algorithm based on the multi-channel Wiener filter Open
Current EEG artifact removal techniques often have limited applicability due to their specificity to one kind of artifact, their complexity, or simply because they are too 'blind'. This paper demonstrates a fast, robust and generic algorit…
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MRI Medical Image Denoising by Fundamental Filters Open
Nowadays Medical imaging technique Magnetic Resonance Imaging (MRI) plays an important role in medical setting to form high standard images contained in the human brain. MRI is commonly used once treating brain, prostate cancers, ankle and…
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VVC In-Loop Filters Open
This paper presents an overview of the technologies for in-loop processing and filtering in the Versatile Video Coding (VVC) standard. These processes comprise luma mapping with chroma scaling, deblocking filter, sample adaptive offset, ad…
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Applications of Savitzky-Golay Filter for Seismic Random Noise Reduction Open
This article utilizes Savitzky–Golay (SG) filter to eliminate seismic random noise. This is a novel method for seismic random noise reduction in which SG filter adopts piecewise weighted polynomial via leastsquares estimation. Therefore, e…
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Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal Open
Recently, the annihilating filter-based low-rank Hankel matrix (ALOHA) approach was proposed as a powerful image inpainting method. Based on the observation that smoothness or textures within an image patch correspond to sparse spectral co…
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A long short-term memory neural network based Wiener process model for remaining useful life prediction Open
An unsuitable type of degradation trend function in the Wiener process-based degradation model will negatively influence its performance when calculating remaining useful life (RUL) predictions. To solve this problem, we propose a Wiener p…
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Compressive Imaging via Approximate Message Passing With Image Denoising Open
We consider compressive imaging problems, where images are reconstructed from\na reduced number of linear measurements. Our objective is to improve over\nexisting compressive imaging algorithms in terms of both reconstruction error\nand ru…
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Compressive Hyperspectral Imaging via Approximate Message Passing Open
We consider a compressive hyperspectral imaging reconstruction problem, where three-dimensional spatio-spectral information about a scene is sensed by a coded aperture snapshot spectral imager (CASSI). The CASSI imaging process can be mode…
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ECG Denoising Using Wiener Filter and Kalman Filter Open
Electrocardiogram (ECG) is a technique of understanding the functioning of heart. Each segment of the ECG signal is significant for the detection of different heart problems. However, some noises generally corrupt the ECG signal. We have p…
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Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution Open
Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodizat…
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Statistical Approach to Compare Image Denoising Techniques in Medical MR Images Open
In medical image processing, magnetic resonance (MR) imaging techniques play an important role. The images acquired are usually affected from various noise such as gaussian noise, salt and pepper noise, speckle noise, periodic noise etc. T…
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Characterization of transfer function, resolution and depth of field of a soft X-ray microscope applied to tomography enhancement by Wiener deconvolution Open
Full field soft X-ray microscopy is becoming a powerful imaging technique to analyze whole cells preserved under cryo conditions. Images obtained in these X-ray microscopes can be combined by tomographic reconstruction to quantitatively es…
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Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition Open
This paper describes multichannel speech enhancement for improving automatic\nspeech recognition (ASR) in noisy environments. Recently, the minimum variance\ndistortionless response (MVDR) beamforming has widely been used because it\nworks…
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Successful optimization of reconstruction parameters in structured illumination microscopy – A practical guide Open
The impact of the different reconstruction parameters in super-resolution structured illumination microscopy (SIM) on image artifacts is carefully analyzed. These parameters comprise the Wiener filter parameter, an apodization function, ze…
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Estimating Parameters of Optimal Average and Adaptive Wiener Filters for Image Restoration with Sequential Gaussian Simulation Open
Filtering additive white Gaussian noise in images using the best linear unbiased estimator (BLUE) is technically sound in a sense that it is an optimal average filter derived from the statistical estimation theory. The BLUE filter mask has…
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Single Channel Speech Enhancement: Using Wiener Filtering with Recursive Noise Estimation Open
This paper discusses the problem of single channel speech enhancement in stationary environments, and proposes Wiener filtering with the recursive noise estimation algorithm. The Wiener filter is a linear estimator and minimizes the mean-s…
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Point spread functions and deconvolution of ultrasonic images Open
This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formula…
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Speckle Noise Reduction of Ultrasound Images Using BFO Cascaded with Wiener Filter and Discrete Wavelet Transform in Homomorphic Region Open
Speckle noise removal is a key issue in ultrasound image processing used for getting important diagnostic information for human body. Speckle noise degrades the visual evaluation of ultrasound images. The main challenge of despeckling is t…
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Regression of environmental noise in LIGO data Open
We address the problem of noise regression in the output of\ngravitational-wave (GW) interferometers, using data from the physical\nenvironmental monitors (PEM). The objective of the regression analysis is to\npredict environmental noise i…
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Deep learning with noise‐to‐noise training for denoising in SPECT myocardial perfusion imaging Open
Purpose Post‐reconstruction filtering is often applied for noise suppression due to limited data counts in myocardial perfusion imaging (MPI) with single‐photon emission computed tomography (SPECT). We study a deep learning (DL) approach f…
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Comparison of Deconvolution Filters for Photoacoustic Tomography Open
In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolu…
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Comparison of Speech Enhancement Algorithms Open
The simplest and very familiar method to take out stationary background noise is spectral subtraction. In this algorithm, a spectral noise bias is calculated from segments of speech inactivity and is subtracted from noisy speech spectral a…
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Data Unfolding with Wiener-SVD Method Open
Data unfolding is a common analysis technique used in HEP data analysis.\nInspired by the deconvolution technique in the digital signal processing, a new\nunfolding technique based on the SVD technique and the well-known Wiener filter\nis …
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Bendlet Transform Based Adaptive Denoising Method for Microsection Images Open
Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements.…
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A SAR Image Despeckling Method Based on an Extended Adaptive Wiener Filter and Extended Guided Filter Open
The elimination of multiplicative speckle noise is the main issue in synthetic aperture radar (SAR) images. In this study, a SAR image despeckling filter based on a proposed extended adaptive Wiener filter (EAWF), extended guided filter (E…
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A Robust Hybrid Watermarking Technique for Securing Medical Image Open
In the aim to contribute to the security of medical image, we present a robust watermarking method which combines discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD).This approach is int…
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Adaptive Wiener Filter and Natural Noise to Eliminate Adversarial Perturbation Open
Deep neural network has been widely used in pattern recognition and speech processing, but its vulnerability to adversarial attacks also proverbially demonstrated. These attacks perform unstructured pixel-wise perturbation to fool the clas…
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Blind Sampling Rate Offset Estimation for Wireless Acoustic Sensor Networks Through Weighted Least-Squares Coherence Drift Estimation Open
© 2014 IEEE. Microphone arrays allow to exploit the spatial coherence between simultaneously recorded microphone signals, e.g., to perform speech enhancement, i.e., to extract a speech signal and reduce background noise. However, in system…
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Models and Information Rates for Wiener Phase Noise Channels Open
A waveform channel is considered where the transmitted signal is corrupted by\nWiener phase noise and additive white Gaussian noise. A discrete-time channel\nmodel that takes into account the effect of filtering on the phase noise is\ndeve…