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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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 ...
2 votes
1 answer
39 views

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 ...
1 vote
1 answer
182 views

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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1 vote
1 answer
32 views

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-...
0 votes
0 answers
65 views

Applying 1D wiener filter radially to 2D image

I am new to image processing. Using python, I have constructed a 1D wiener filter from the power spectrum of a Noisy Image, with Noise as a function of k. They both have the same dimension which is ...
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1 vote
1 answer
109 views

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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0 votes
0 answers
45 views

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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0 votes
0 answers
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Filter signal with extreme outliers in one direction

I want to fit a smooth curve to my raw signal (blue). It's roughly a sinusoidal shape but with extreme outliers in one direction (notice the points that are much lower than expected). I've tried to ...
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1 vote
1 answer
72 views

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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6 votes
2 answers
674 views

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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0 votes
0 answers
332 views

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 ...
5 votes
1 answer
107 views

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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-1 votes
1 answer
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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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6 votes
2 answers
180 views

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 ...
2 votes
1 answer
129 views

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 ...
0 votes
0 answers
38 views

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 ...
6 votes
1 answer
147 views

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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1 vote
1 answer
175 views

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 ...
1 vote
2 answers
126 views

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 ...
1 vote
1 answer
100 views

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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1 vote
0 answers
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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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7 votes
1 answer
180 views

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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5 votes
1 answer
68 views

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 ...
-1 votes
1 answer
48 views

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 ...
7 votes
2 answers
793 views

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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0 votes
1 answer
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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 ...
0 votes
2 answers
93 views

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. ...
0 votes
1 answer
175 views

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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0 votes
0 answers
496 views

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 ...
1 vote
1 answer
88 views

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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0 votes
0 answers
33 views

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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2 votes
1 answer
45 views

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 ...
4 votes
2 answers
153 views

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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6 votes
2 answers
663 views

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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0 votes
1 answer
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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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1 vote
0 answers
30 views

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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1 vote
0 answers
59 views

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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1 vote
2 answers
87 views

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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3 votes
2 answers
81 views

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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5 votes
1 answer
88 views

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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1 vote
1 answer
110 views

Understanding noise removal method using wavelets

I am trying to understand how wavelet transform can be used to denoise a time series or signal and how to plot the scalogram image. My signal has a lot of fluctuations and as such I am finding it ...
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2 votes
1 answer
41 views

Enhancement by adaptive wavelet shrinkage denoising

I was wondering does anyone know any programming library or a way that can help me implement this algorithm.
5 votes
3 answers
143 views

How to denoise a video stream from poor CCTV lighting

I have grainy CCTV footage that will need some amount of clean up. I request for ideas on the best way to clean out the noise. I am attaching a frame extracted from the video here for hints on the ...
1 vote
0 answers
36 views

What are the wavelet packet functions and how are they different from the wavelet and scaling functions?

I understand that in the decomposition process, wavelet and scaling functions are used to split the signal to approximation and detail coefficients. Most of the time I saw the wavelet and scaling ...
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5 votes
1 answer
115 views

Removing Gaussian Noise from a Signal to Get Minimum Value

I have a signal that has a minimum value that I'm trying to read. The issue I'm having is that the signal is spread out by gaussian noise. I have the signal at a lot of timesteps (and expect the ...
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1 vote
0 answers
497 views

Implementation of Cepstrum in Python

Actually I want to denoise a signal. I know how can I implement FFT in python to denoise it. This is the implementation which I use(From this Kaggle notebook): But I don't know : How can I use ...
7 votes
1 answer
100 views

Recommended Resources / Literature Search Terms for a Solutions to a Specific Kind of Multi Harmonic Signal Structure

Hopefully this isn't considered too off-topic. I'm working in industry these days and came up with a solution to a signal processing problem we'd been facing. I'd like to get a sense as to whether ...
1 vote
0 answers
42 views

Why should wavelet re-synthesis produce an output when the main component is suppressed and what does this mean for denoising?

I understand that aliasing occurs in DWPT if the wavelet used is of low order since the "filters" are not perfect and the combination of down sampling and overlapping between bands causes ...
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6 votes
1 answer
241 views

A Simple Algorithm to Filter / Smooth / Denoise a Noisy Staircase Graph

Is there a way to remove the noise and smooth the graph into a staircase graph.
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0 votes
0 answers
26 views

Discrete wavelet center frequency

I am understanding that mother wavelets have a center frequency. Wavelets are limited in duration and oscillate then decay, so the center frequency is the mid pulse of the wavelet or so. But my ...
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