# Tag Info

Accepted

### Deconvolution of a 1D Time Domain Wave Signal Convolved with Series of Rect Signals

Solving a deconvolution isn't easy even in simulated environment not to mention in practice. The main trick to solve it is using the proper model / prior for the problem and very good measurements (...
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• 41.4k
Accepted

• 41.4k
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### How to Solve Blind Image Deblurring with Total Variation (TV) Prior Using ADMM?

First, let's analyze the problem by formulating it. The model is given by: $$\boldsymbol{y} = H \boldsymbol{x} + \boldsymbol{n}$$ Where $\boldsymbol{y}$ is the given image, $H$ is an unknown ...
• 41.4k
Accepted

### How to Solve an Image Deblurring Problem by Variational Methods Using ADMM?

Remark: This is adapted from How to Solve Image Deblurring with Total Variation Prior Using ADMM? Formulation of the Problem I am solving the problem under the following assumptions: The blurring ...
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### How to solve ADMM for TV Minimization Problem For Different Sizes $A$ and $x$ in $Ax=b$

The Error in the Model The problem is in the dimensions of the Linear Operator $A$ in your model compared to the Data Matrix $X$. The number of columns of the matrix $A$ must match the number ...
• 41.4k
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### What Is the Difference Between MRF and Total Variation in Noise Removal?

These are two different concepts that you talk about. First, MRF gives you a framework to do discrete optimization of problems, which respect the Markovian property, that is a pixel is conditioned ...
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### Deconvolution of a 1D Time Domain Wave Signal Convolved with Series of Rect Signals

Actually I have a similar problem like yours. But in mine, the objective function is not like rectangular pulse but just spikes as shown below. I work in ultrasoinc testing field. So, this example is ...
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Accepted

### Gradient of Total Variation (TV) Norm in Total Variation Denoising

I am by no means an expert on total variation, however I think you should check out this Wikipedia page. It doesn't directly answer your question, but I believe the lemma below illustrates the ...

### Gradient of Total Variation (TV) Norm in Total Variation Denoising

To obtain the Gradient of the TV norm, you should refer to the calculus of variations. By examining the TV minimization with Euler-Lagrange equation, e.g,, Eq. (2.5a) in [1], you would see the ...
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