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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1answer
646 views

How to calculate IDFT this signal? [closed]

$X(jw) = 1 + \frac {jw+3}{jw+4}$ what is the IDFT of this signal?
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How do you deconvolve irregularly sampled points?

$f:\mathbb{R}^n\rightarrow\mathbb{R}$ is a signal and $g:\mathbb{R}^n\rightarrow\mathbb{R}$ is a known point-spread function (say, a Gaussian). A system samples $f\star g$ at a known sequence of ...
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What's the Difference between Convolution Kernel and Point Spread Function in the Context of Image Convolution?

When you use the deconvolution method to make the blurry image sharper, you will have to estimate the Point Spread Function. Is there a difference between this PSF and an image kernel? Second ...
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3answers
289 views

Deconvolution (Linear Convolution) with an Under Determined System of Equations?

If I have a measured signal $\mathbf{y}$ which is the result of the true signal $\mathbf{x}$ convolved with another function (linear and not circular convolution), I always seem to get an ...
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1answer
85 views

Why Does Image Deconvolution Still Work with Image without Sharp Edges?

Why does image deconvolution still work with image without sharp edges? Take this image for example:
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0answers
78 views

What are the historical milestones in image Deconvolution? [closed]

Norbert Wiener came up with the Wiener Deconvolution in 1949 or something like that. But what happened after that? When was Richardson-Lucy deconvolution developed for example? And what happened ...
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2answers
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Differences using Maximum Likelihood or Maximum a Posteriori for Deconvolution / Deblur?

Are there any differences if you use Maximum Likelihood or Maximum a Posteriori to estimate the Point Spread Function for image deconvolution?
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1answer
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SVD is not applicable to time series analysis?

I am studying a deconvolution problem for which observations include noise. I am considering using one of several common regularization methods, including Tikhonov's solution, truncated Singular Value ...
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2answers
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How Is the Formula for the Wiener Deconvolution Derived?

Wikipedia shows this formula: $$ \ G(f) = \frac{H^*(f)S(f)}{ |H(f)|^2 S(f) + N(f) } $$ But how is this Wiener deconvolution formula derived and where does the squaring ($|H(f)|^2$) come from?
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132 views

Estimation of Input Signal to Obtain the Desired Output Signal for an Unknown Filter

Suppose $h(n)$ is a finite impulse response which is unknown. We can feed any input signal $x(n)$ into the system and observe the corresponding output signal $y(n)$. From this, is it possible to ...
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1answer
456 views

How to choose a phase for the deconvolution of an autocorrelation?

Say I have a function, $C=C\left(x\right)$, whose fourier transform is denoted by $c=c\left(k\right)$, i.e. $C\left(x\right)=\sum_{k=-\infty}^{\infty}c\left(k\right)\chi\left(x\right)$, where $\chi\...
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0answers
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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 ...
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2answers
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Performing a Deconvolution

So I have the following data: ...
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1answer
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Using DFT Circular convolution property

I am trying to make proper use of the circular convolution property of DFT. I was taught that the DFT of x[n]*CircularConv*y[n], would be equal the product of the ...
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2answers
508 views

Deconvolution of Images - How To?

I'd like to do a deconvolution of image. For example for convolution I'm using a $3\times 3$ mask with all elements $= 1$: $$\begin{bmatrix}1 & 1 & 1 \\ 1 & 1 & 1 \\ 1 & 1 & 1\...
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1answer
825 views

Deblurring algorithm to precede thresholding - speed over accuracy

I'm writing an app that recognizes Sudoku puzzles from a camera input. I'd like to remove camera blur from the images to improve recognition. Here is an example image: Since I'm processing a ...
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1answer
634 views

What are some suitable methods for removing low-frequency line noise from measured data prior to system identification/deconvolution?

I am performing a system identification by striking an experimental model with an instrumented impact hammer and measuring the strain response. The timebase for the recorded signals is 5 microseconds ...
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1answer
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Deconvolution in Python

I'm trying to use and understand SciPy's deconvolve for a project I'm working on. I'm having some trouble understanding how to use it. What I would like to do is to take two PMFs from discrete ...
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2answers
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How to Estimate the Input for a Convolution Given the Filter (Impulse Response) and the Output of the Convolution

I understand how to find the output from the input with an impulse response, but how can I go about finding the input if given the other two? I have $y[n] = [-1, -1, 11, -3, 30, 28, 48]$ and $h[n] = [...
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1answer
394 views

How to Select Point Spread Function Empirically for Image Deconvolution?

When the captured image is blurring, one way of obtaining a clear image is via image deconvolution technique. In order to perform deconvolution successfully, usually we need to pay attention to the ...
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3answers
607 views

Recover Filter Coefficients from Filtered Noise

I have a digital signal which may be represented as a pulse noise source filtered with an FIR (finite impulse response) filter. Suppose that the noise consists of discrete pulses (nonzero samples ...
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2answers
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How to Deduce a Linear System's Impulse Response from a Set of Input and Output Signals?

I want to know how to solve those types of problems.. is it by inspection ? Consider the linear system below. When the inputs to the system $x_1[n]$, $x_2[n]$ and $x_3[n]$, the responses of the ...
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1answer
620 views

Audio Signal Noise Filter Problem

I'm currently working with audio signals and have a problem: C = A*B + N, where C = recorded signal from microphone consisting of: A = known music file data played on speakers next to microphone ...
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1answer
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Deconvolution - Richardson Lucy vs. Wiener Filter

I am studying some deconvolution techniques, In order to remove motion blur, like: Richardson-Lucy Wiener Are there any pros / cons of using one versus another? For example which are the pros / cons ...
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2answers
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Using reference objects to estimate the point spread function?

I have a well-defined object and a clear image matrix of it. In subsequent frames the object moves, causing motion blur. I want to use the object as a reference to "guide" the deconvolution and ...
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12answers
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Deconvolution of 1D Signals Blurred by a Gaussian Kernel

I have convolved a random signal with a a Gaussian and added noise (Poisson noise in this case) to generate a noisy signal. Now I would like to deconvolve this noisy signal to extract the original ...
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1answer
382 views

Deconvolution Question on Article “Deriving Intrinsic Images from Image Sequences” by Yair Weiss

there are n derivative filters: $f_i$, and denote $f_i^r$ as $f_i$'s reverse filter such that $$f_i(x,y)=f_i^r(-x, -y)$$ $r_i, f_i$ given, to find $r$ from the equations: $$f_i * r = r_i, (1 \leq i \...
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2answers
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Using the Inverse Filter to Correct a Spatially Convolved Image (Deconvolution)

As part of a homework assignment, we are implementing the Inverse Filter. Degrade an image then recover with an Inverse Filter. I convolve the image in the spatial domain with a 5x5 box filter. I FFT ...
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2answers
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What Are Less Computationally Demanding Alternatives to the Viterbi Decoder?

What are less computationally demanding alternatives to the Viterbi Decoder? Ideally what I would like is a list of the most commonly used approximate methods, along with brief pros and cons.