Questions tagged [blind-deconvolution]

is a set of methods aimed to solve the problem of recovering (reconstructing) precise version of a distorted (transformed) signal, where the distortion (transform) matrix (kernel) or the Point Spread Function (PSF) is unknown.

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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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368 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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Estimate peak width from a vector that is a superposition of unknown number of identical Gaussian peaks with different heights?

If you have a vector that is a superposition of an unknown number of identical Gaussian shaped peaks/impulses of unknown width (but all the same width) and different amplitudes (with Poisson or ...
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Finding the Best Gaussian Smoothing Kernel to Minimize the Discrepancy Between Two Images

Suppose we have two grayscale images, $A$ and $B$. $A$ and $B$ very strongly resemble each other, such that the mean of the absolute difference $\lvert A - B\rvert$ is fairly small. Suppose further ...
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182 views

Extracting the talking (lyrics) from an audio in python [closed]

I am new in signal processing and I want to extract the talking (lyrics) of a person from a sound so I can analyze it ;another application would be if that person is talking and there are many sounds ...
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45 views

Error plot between known and estimated data

The channel is an FIR model with input $u$. The input takes in values which are symbols from some constellation. Using an equalizer such as the Least Mean Squares (LMS), I estimate the input to the ...
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2answers
2k views

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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256 views

Why Sparse Priors Like Total Variation Opts to Concentrate Derivatives at a Small Number of Pixels?

When performing image deconvolution (deblurring), people often make use of priors to get rid of the illness of the problem. One very common prior is total variation, a sparse prior. Compared to ...
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188 views

Quantitative comparison of scaled-, delayed- and warped-signals

The following question is detailed in 1D, with time as the ordinal variable. Similar questions could apply in other dimensions. In several signal processing techniques, such as blind source ...
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1answer
106 views

How is Point Spread Function (PSF) related to Image Priors in Blind Deconvolution?

We are researching for our thesis about enhancements in Blind Deconvolution Image Deblurring Algorithm Applied in Image Restoration. What really is PSF? Is it one kind of image prior? What do these ...
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ICA for blind source separation clarification question

I'm currently trying to implement FastICA for blind source separation from scratch. The code below does not generate W, the umixing matrix, correctly. When I matrix multiplied the outputs ...
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968 views

Blind deconvolution implementation, Python, Shalvi-Weinstein

I'd like a 1D blind deconvolution implementation in Python. I read Shalvi and Weinstein 1990 (on the recommendation of Yair Weiss) and it appears relatively simple. However I can't find an existing ...
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194 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 ...
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Help in problem formulation for estimation of image as a feature vector - SISO or MIMO FIR channel model?

Based on the paper Blind Image deconvolution: A feature vector is a list of numbers used to represent an image. The feature vector for my case takes values as symbols $-1,1$. An instance or an ...
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352 views

Implementing blind deconvolution in MATLAB

I want to implement blind deconvolution for the signal $ r(n) = h(n) \star s(n) + a(n)$ in MATLAB where $r(n)$ is the recorded speech $h(n)$ is impulse response of room acoustics $s(n)$ is desired ...
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Matlab: How to apply constant modulus algorithm in wireless communication

I am trying to apply the Constant Modulus Algorithm which is a blind equalization algorithm in CDMA communication. I am following the code for CMA and a great explanation given in link MATLAB : Proper ...
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Constant Modulus Algorithm and the gradient operation

CMA is a blind channel equalization algorithm with the details presented above. I am facing 3 difficulties and shall appreciate help Q1: Does $H$ and the bar over $\bar{y_k}$ represent the Transpose ...
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38 views

Extract a square-shaped signal which lies in a specific range

I need to extract (estimate) a square-shaped signal from the main signal. This square-shaped signal should be located within a specific range, in fact all we have to do is to estimate its height. A ...
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Need suggestions on the class of blind adaptive filters that can be used in my situation

I have 2 satellite transponders closely situated, transmitting the same signal. At the receiver I receive this composite signal. I have to equalize it in such a way that the demodulator sees only one ...
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186 views

How to deconvolve dependent part of signal from independent part?

I have a problem of the following form. There are two signals, x(t) and y(t). The model for the system is such that: $$x(t) = x'(t) + f(y(t))$$ where $f(y(t))$ is a variable offset introduced by ...
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1answer
815 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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2answers
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Is there a way to reduce the covariance matrix of several source signals to the dominant source signal?

The problem I have can be seen in the context of DoA estimation or blind source signal separation and similar fields, where several source signals are observed by several antennas (or by an antenna ...
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blur PSF modeling for small stright camera movement

I am interested in reovering images affected by blur of known orientation and known span. Camera movement during capture is very small, blur span is of about 0-4px. What is the most accurate way to ...
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Blind 1D equalization/deconvolution with some knowledge of filter kernel

Let $s_{\rm out}[n]$ be the 1D output signal of a system, $s[n]$ be the input, and $k[n,q]$ be the filter kernel for an element $n$ and for fixed value $q$. Then: $s_{\rm out}[n] = s[n] \ast k[n,q]$ ...