Questions tagged [denoising]
Denoising is a collection of techniques to remove unwanted noise from a signal. Typically this is done by filtering, but a variety of other techniques is available. Often combinations are used in sequence to optimize the denoising.
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PSNR decreases while denoising
I currently am trying to portray PSNR's ability to measure noise in an image. The PSNR is said to be high (around 40 dB) if there is a low amount of noise in the 2D signal.
In my experiment I have ...
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Avoiding latency distortion at high denoise levels with DWT
I am denoising biological signals using the DWT, and for UI reasons would prefer the smoother waveform afforded by denoise level 5. However, higher denoise levels seem to distort the latency of ...
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How do I eliminate background noise？
After I use deep learning algorithm to enhance the speech, the speech will still have a weak background noise.The background noise of this audio has little effect on the calculation of SNR, but it ...
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How to Dereverberate Speech taken in an Auditorium with Reverberation Time of 3.8 to 4 seconds
I'd like to cancel echoes from a Talk recorded in a large extremely reverberant auditorium. It's unintelligible as recorded, and I'm hoping to make it intelligible by echo cancellation.
Audio was ...
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Adaptive filtering [duplicate]
I want to mention upfront that I'm not very experienced in this field.
I have a signal $u(k)$ that I get from a black box simulation (sampled irregularly). The signal looks like this:
The blue signal ...
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How do I remove the aurora from an image to enhance the background stars?
Most auroral pictures are post-processed and enhance the aurora to such an extent that you don't see the background stars. Suppose I have a photo of the night sky with an aurora, taken with my phone ...
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78RPM 1900's records - is there more in the high end signal than humans hear, and could ML extract it?
Consider some record with Enrico Caruso singing, anno 1904 or so. Back then, records did not employ pre-distortion such as with RIAA curve to then later, during playback, invert the curve, to get a ...
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Brrrrrrrrr clanky clank VHS noise
I have audio of VHS with speech and music, and with noise of frequency that's higher and lower than most of human speech, with apparently least but still significant energy in-between, that cannot be ...
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Noise leakage problem with least square estimation in the frequency-distance domain
I have data $d$ recorded from an antenna of sensors. These data are composed of a Gaussian noise $n$ and a signal $s$ which I try to estimate. This signal propagates on the antenna with frequency ...
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Basic audio denoising in the frequency domain using minimum statistics?
I'm trying to do some example elementary denoising of the audio signal. Let's say input is speech with constant traffic background noise.
First I calculated block-based overlap-add Fourier transform (...
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What process could generate this kind of noise in the multitaper spectrum?
I am recording some data for scientific purposes (it is neurological data), and the data is corrupted by some very strange noise. At multiples of about 700 Hz (slightly differing on different days) ...
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Relationship between different 2D FFT/Fourier domain window sizes?
hope everyone is enjoying their holidays. I'm a PhD researcher and I have an idea to filter an image using FFTs but I would like to try capture information at different scales using multiple window ...
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Bibliographic References on Denoising Distributed Acoustic data with Deep Learning
Distributed Acoustic Sensing (DAS)
I have an iDAS (intelligent distributed acoustic sensing) dataset obtain from an undersea optical fibre. iDAS data have a 2D dimensional representation. On the one ...
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Edge / Pixel Type (Homogenous, Edge, Texture) Classification as Part of an Image Denoising Procedure
For most noise reduction algorithm, the same process is applied to every pixel no matter
the pixel belongs to one of three types of pixels such as homogeneous regions, edges or textures.
Different ...
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Removing white reflective pixels from scanned RGB image (Python - preferably OpenCV)
The images above are tiles taken from a scanned painting. It's easy to see where there are tiny reflections scattered throughout. I wish to remove (or diminish) the tiny reflections somehow, across a ...
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bias-variance trade-off in image denoising
I am reading the paper A Bias-Variance Approach for the Nonlocal Means.
One sentence from the paper is as follow:
To discuss the tuning of parameters of the NLM, we interpret this
choice as a bias-...
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If I know the RMS noise/the variance of a DC measurement, can I simply subtract it from the measurement?
Let's say I have an electronic system that's taking a measurement. It provides a simple bipolar excitation current to a resistive load (bipolar square wave so as to cancel out thermal emf), puts it ...
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Weird filtering result
Im filtering some ecg data for mainly just powerline noise (50 Hz), but get some weird result between the R-peaks (main spike). I have just done some tried with some basic filtering like this:
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understand short time fourier transform
I am reading this paper for signal denoising. In the paper, the authors says
The core concept in this paper is to compute a regression between a noisy signal frame and a clean signal frame in the ...
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Can the deconvolution Wiener filter reduce noise without having a blurred image?
I am trying to denoise many several noises with several filters for a research i have, i found a deconvolution Wiener filter made by "mr.tranleanh" on Github, as you can see here .
what I ...
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FFT denoising vs low pass filter
Say I have a noisy signal in which I want to denoise.
There's two methods I'm considering
FFT denoising, where I take the FFT of the signal and then threshold somewhere, attenuate all the frequencies ...
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Denoising a Grayscale Image Using Random Matrix Theory (RMT)
I am applying RMT on grayscale images. Basically for any matrix, it consists of two parts: one is pure noise and other is information. Now, to distinguish noise from information, RMT comes handy. We ...
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Why NMSE is the same as output SNR but with an opposite sign?
I am doing denoising on signal, and as performance measures Normalized Mean Squared Error (NMSE) and output-SNR between original/clean and denoised signals are used.
However, for several cases the ...
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The Effect of Spatial or Temporal Averaging on Noise Properties
I generate two noise images using MATLAB's function imnoise().
If I average the two noise images, the resultant image looks like the original noise
image but only ...
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Hankel Matrix SVD Denoising
I have performed Hankel Matrix Singular Value Decomposition de-noising to smooth out my univariate time series. It is the close price of EUR/USD exchange rate. Here is a picture:
The problem I have is ...
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Removing the Dot-Patterns Like Noise
I am dealing with an image restoration problem with noisy measurement. I use the classical total variation norm to remove the noise, specifically, the TV-$L_2$ problem. I used the famous Lena image ...
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Solving a Weighted Basis Pursuit Denoising Problem (BPDN) with MATLAB / CVX
Following up from an answer by @Royi on adding weights to BPDN problem , I would like to use CVX to test this approach. How can we formulate in CVX the regularized LS L1 norm with weights given by a ...
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Does BM3D really need the noise power spectrum beforehand?
I'm at the moment trying to implement a neural network which uses BM3D as a preprocessing step. The problem is, when using the python implementation of BM3D from the paper Collaborative Filtering of ...
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How to remove heartbeat signal from blood pressure signal?
I am working on a medical engineering project that involves processing signals received from a human body. We use a sensor to record the blood pressure, $B(t)$.
However, if you put your finger on many ...
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How to predict the final noise after adding two or more noisy discrete signals?
Is it possible to accurately predict the noise level if we add two or more noisy signals. For the sake of simplicity, let us say, the noise is independent and Gaussian.
Suppose we wish to add signals $...
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Remove Noise from Discrete Signal with given Noise Model
I am interested in finding the true signal $p \in \mathbb{R}^D$ of an observed discrete signal $t \in \mathbb{Z}_{+}^D$.
I know that each observed $t_{i}$ with $1 \leq i \leq D$ is the result of a ...
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Solve Efficiently the 1D Total Variation Regularized Least Squares Problem (Denoising / Deblurring)
How to solve a 1D Least Squares with Total Variation Regularization?
I know gradient based methods, I wonder how much faster / efficient I can get.
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How to Remove Temporal and Fixed Pattern Noise and Apply Tone Mapping?
I have a video, whose frames I have extracted and require to work with. 16 bits and grayscale images.
My task is to improve the quality of the images, by removing the noise + adding tone mapping and ...
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Verifying if noise is gaussian in non-time series data
I'm trying to figure out if the noise in my experiments is gaussian or not.
I don't have time series data.
I first configure my system and then run some software application's and measure the average ...
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How to Solve Image Denoising with Total Variation Prior Using ADMM?
I was looking at some articles or Wikipedia on denoising images using the Total Variation norm. The setup is the Rudin Osher Fatemi (ROF) scheme, and the corresponding equation is:
$$
F(u)=\int_{\...
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Digital Filters
If I want to remove the baseline drift in my ECG signal, which digital filter should be used without distortion and shift in my filtered output?
What are the necessary things I have to look for the ...
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GPS | Retain Signal Tracking after Noise Bound
I have an IF data, 2 seconds signal sample from only one GPS satellite, I know the PRN number of the satellite.
...
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How to filter sudden spikes and baseline changes in microphone signal?
The orange is a signal I recorded, the blue - my first restoration attempt, after which I decided to ask.
The signal is audible, however there are 2 types of defects 1) baseline changes 2) sudden ...
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Pre-Processing Wi-Fi Channel State Information (CSI) Data
I was successfully able to collect some CSI data using the existing tool(s) on GitHub (https://github.com/StevenMHernandez/ESP32-CSI-Tool). The CSI data is a pair of imaginary and real number which ...
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Adding noise to real MRI data
I designed an algorithm for MRI data denoising which has good properties under heavy Rician noise (sigma is greater than 80). The method was tested on some phantoms and Rician noise generators. Now I ...
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Deconvolution of sidelobes in a point spread function?
It seems that most deconvolution algorithms mainly handle the main lobe of a point spread function (PSF) and assume that sidelobes can be safely neglected.
For a direct algorithm trying to perform a ...
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Image noise reduction
I have an image of a cross-section of soil where the main object of interest are the plant roots.
I would like to segment or extract the roots from the background noise of the soil itself and other ...
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Is it possible to remove the non-random noise in the signal by averaging?
Ex: We're measuring vibration Frequency response of a structure, and at the same time there is a constant source of vibration (noise) from a pump. The pump is exciting the structure by sinusoid ...
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What is the advantage of Wiener filter for noise reduction of a 1D signal?
I have a 1D signal, acquired by an accelerator sensor that measure the vibration of a structure. What is the advantage of using a Wiener filter for noise reduction compared to the other (more classic) ...
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Time averaging denoising signal
I would like to use time averaging technique for denoising vibration signal, using the below function, how do we choose the appropriate parameters D and N for optimal denoising !
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Noise removal where gains are >1
I am currently working on some noise removal algorithms and have come across what seems to be an oversight in the design of some of these algorithms.
Two of the algorithms I am looking at use the PSD ...
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Logarithmic Amplitude Spectral Subtraction
I'm diving into audio processing and I'm trying to wrap my head around spectral subtraction. I learned there are different approaches do it based on power, magnitude, oversubtraction. My task is to ...
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What is the best estimate of a signal given multiple noisy realisations
I assume that the noise corrupting the sought-for signal is [Edit: Gaussian] white noise of zero mean and unknown variance. Is the optimal solution simply the mean over the realisations (the ensemble ...
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Help with denoising signal and periodogram analysis resources
This is a cross posting from the crossvalidated stack exchange as I thought this may be a better forum to ask.
I have a dataset consisting of respiratory time series signals of different lengths ...
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What Are Intuitive Explanations for Shrinkage in the Context of Image Denoising?
I have occasionally come upon the term "shrinkage", mostly in the context of denoising methods.
My rough understanding is that it refers to the part where the real distribution might not be ...
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