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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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 ...
823 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 ...
2k views

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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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 ...
87 views

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 ...
253 views

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 ...
1k 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 ...
56 views

Estimating Convolution Kernel from Input and Output Images

Given an original image and a convolved version of it, I need to calculate the convolution kernel. For example, given: and I would like to calculate the convolution kernel that generated the second ...
288 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 ...
143 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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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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Estimating an Image Filter from Examples

I am sure this question must be fairly easy and could have been answered on this site but perhaps I am not finding the right keywords to search for it. I would like to know what are the common ...
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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 ...
391 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 ...
233 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 ...
125 views

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 ...
223 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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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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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?
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 ...