# Questions tagged [deconvolution]

in mathematics, the inverse operation of convolution signals. In general, the purpose of deconvolution is to find solutions of the convolution equation defined as: f * g = x. Where h is the recorded signal, and f is a signal that you want to recover, and we know that the first signal is obtained by convolution of the second with some known signal g. If the signal g is unknown, it has to be estimated (eg. statistical estimation).

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### How to properly match bit growth of a FIR filter with a reference value

I am trying to implement a chain of CIC/FIR filters on an ZYNQ FPGA. Using the Xilinx FIR compiler works fine so far but I am unable to properly get all the math. At the moment I have 2 chains of ...
236 views

### Deconvolution of non-stationary, 1-D signal?

I have a time series that has been measured after convolution with a moving average filter. Knowing the parameters of the moving average filter, is it possible to reconstruct/constrain the values of ...
58 views

### Approximating inverse of unstable difference of Gaussians filter

I am trying to invert a difference of Gaussians (DoG) filter. The inverse is not stable and so I am trying to find an approximation applied to a specific input. The DoG filter increases contrast at ...
74 views

### calculate or decompose a Fourier transform signal amplitudes with unknown weights on sources

migrated from math-se... I am trying to calculate , or approximate the solution of following Fourier-sine transform problem that can be expressed as a contributions of periodic sources $f_i(x)$ and ...
275 views

### NMR spectrum deconvolution on Matlab

I am doing an NMR experiment by applying an rf signal to a sample which is mounted near a magnet and in the end I get an FID (free induction decay) and do Fourier Transform to this FID . So we have a ...
42 views

### Deconvolution: how to build Discrete-Time Impulse Response matrix?

I am reading a paper about the Hunt problem: Consider the iput given by $$e(t) = \mathrm{e}^{-\left(\frac{t-400}{75}\right)^2} - \mathrm{e}^{-\left(\frac{t-600}{75}\right)^2},\quad 0\leq t \leq 1025$$ ...
34 views

### Unexpected results of deconvolution with scipy.deconvolve

Below I have plotted the signal (Lifetime decay) I am trying to deconvolve from a known impulse response function (IRF), as well as the IRF itself. I'm using scipy.signal.deconvolve. Please note for ...
84 views

### How to update point spread function of blind deconbolution by conjugate gradient?

There is an unblurred image $g$ and a blurred image $x$. Their relationship is expressed by the following formula using $psf$(point spread fucntion, size is $5×5$ kernel). $g = x \otimes psf\tag 1$ ...
70 views

### 2D Deconvolution using a non-gaussian mask using C++

I am currently working on a project, where we record an electron beam profile using a target. The obtained image is a result of convolution of the actual beam profile and the aperture wherein the ...
64 views

### How to estimate the system characteristic function given experimental input and output

I have experimental signals $y_i(t)$ for $i = 1,\ldots,n$ that correspond to different excitation inputs to a system $x_i(t)$ for $i = 1,\ldots,n$. The goal is to find the system characteristic ...
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### Adapting Richardson Lucy (RL) Deconvolution for Shot Noise Limited Coherent Imaging

I am an experimental physicist who is collecting a series of coherent imaging of trapped gas. If you are familiar with phase contrast imaging, you may understand what I mean by coherent imaging. The ...
300 views

### Can we use SVD to solve single channel deconvolution problem?

I have seen using singular value decomposition (SVD) to solve deconvolution problem for example truncated SVD (TSVD) . It appears there is also a connection between Tikhonov regularization and SVD. My ...
73 views

### Why is the term deconvolution used more for signals and not so much (or at all) for systems?

Wikipedia defines mathematical deconvolution here, and with the examples given and my experience, what I've read over the years is that deconvolution is used to determine an input signal provided a ...
339 views

### how to get an input test signal for convolution/ distortion method

i am trying to do some experiments with Total Harmonic Distortion. According to ...
481 views

### Problem implementing deconvolution to recover an Impulse Response

I’m new to DSP programming and I’m trying to learn a bit about convolution and deconvolution and FFTs. I have a project where I am taking a signal (a sine sweep) and convolving it with a shorter ...
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### variation of the source separation problem

I have four sensors which make measurements $y_k(t)$ that can be modeled as complex time series: $y_1(t) = h_1(t) * x(t) + n_1(t)$ $y_2(t) = h_2(t) * x(t) + n_2(t)$ $y_3(t) = h_3(t) * x(t) + n_3(t)$...
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### Deconvolution of signal with harmonic distortion

I came across these measurements done using a stepped sine sweep covering only some frequencies (~800 frequency points). I would like to get an impulse response from these measurements to convolve ...
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### How to handle zeros before FFT convolution / deconvolution?

I would like to calculate the input function (unknown) by deconvolution of the output and the "system response" signals. The output is a finite signal from a measure device so it presents ...
22 views

### Unexpected result of motion-blurred image deconvolution

In my case I have some images, captured by CMOS-camera (global shutter) during non accelerated motion (with fixed illumination and focus and known velocity and exposure time, so field of view travels ...
41 views

### How to smooth wiener deconvolution result in Python?

I'm wondering if it is possible to smooth the estimated response from a Wiener deconvolution in order to have a better representation of the original signal and to remove the side lobes. (Here an ...
9 views

### Upsampling class activation maps for discriminative feature localisation

I am currently reading a paper by on learning deep features for discriminative localization where the authors propose to use class activation maps to learn discriminative localised features. The ...
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### Computing the pseudo inverse filter from the SeDDaRA blind deconvolution process

I'm trying to apply the non-iterative method in the research paper Efficient blind deconvolution of audio-frequency signal to my ultrasound data. I'm at the point where I believe I've calculated the ...
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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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### Deconvolution with noisy measurement of impulse response function

I observe a noisy 1D signal that has passed through some linear time-invariant filter: $$z(t) = (h\star x)(t) + n(t)$$ where $h(t)$ is the filter, and I am hoping to recover $x(t)$. $n(t)$ is some ...
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### Richardson-Lucy iterative deconvolution is producing erroneous deconvoluted images

I am working on producing deconvoluted image from degraded image where the process of degradation is known to be linear and space invariant. I have used Richardson-Lucy iterative deconvolution method ...
78 views

### Recover an OFDM signal affected by AWGN

I have an OFDM signal affected by AWGN, if I know the power of the gaussian noise, can I recover the OFDM signal? Can I perform deconvolution to recover the original signal? thanks
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### Receiver function, frequency domain deconvolution not giving logic results

I'm working on some code for receiver function method in seismology. For anyone one not into the topic, it's just a deconvolution of two time series (seismograms). This can be done in the time domain ...
158 views

### How to water level deconvolve a noisy signal if i have a zeros and poles file?

Thanks for your time and help! I am working with Apollo project passive seismic experiment (PSE) data, and I have a large set of seismic records (on digital counts) and the corresponding file of poles ...
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### Whats the Correct Approach to Estimate the PSF of a Moving Detector

In lab, I did a bunch of scans using a radiation source and a detector. My source emits a gaussian beam (whose dimensions I know), and my detector is a uniform 7mmx7mm square. These are stationary and ...
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### Scipy Deconvolve help

I was playing with the deconvolve method in scipy and I can't seem to get it working properly (I am still really new to DSP/deconvolution). I convolved a gaussian with a fwhm of 2.0e-9 with a ...
358 views

### Deconvolve using divsion of FFT of shifted signal in time domain

I have FFT of two signals. Y=120 , Y1=80 Hz. to convolve in time domain I can convolve them using their ffts. as ...
438 views

### python rewrite lfilter (iir) with for

It's a beginner question, but useful to users from python - signal.lfilter, I was using lfilter from Find reverse one pole ...
195 views

### noise in audio deconvolution result

I'm testing some code to perform deconvolution of two audio signals to recover the impulse response. Presently, as part of testing, I am simply deconvovolving two identical signals. I have the ...
82 views

### deconvolution challenge

OK hive mind... i have two identical fixed-size signal buffers, each containing 4 channels of audio. I perform a 2d REAL to COMPLEX FFTW_ESTIMATE on both, resulting in two identical spectra of the ...
88 views

### Enforcing size to match Convolution using 'same' property & Enforcing Circulant Matrix (Like DFT Based Convolution)

The original problem was from this link about coding de-noising an audio signal. Because my reputation points disabled me to comment, I have to ask a separate question here. I don't quite ...
125 views

### Fourier domain division causing translation

I am trying to find the correct filter to convolve with an image so they have the same PSF. I have the final PSFs of both images: A: PSF of the image with the wider PSF. B: PSf of the image with ...
58 views

### Isolating overlapping image

Using a diffraction grating in front of my smartphone's camera, I can decompose light sources into their spectral components. The problem is that the background is not always dark and there might be ...