Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [total-variation]

The tag has no usage guidance.

0
votes
0answers
19 views

How would i get the total variation demonising for an X-ray image

Total Variation for an X-ray image. using rof model Is there any function to find total variation. TV with respect to I by $$\sum\sqrt{i x^2+i y^2}+\lambda\|i-g\|$$ $I$ is the denoised Image $I x$ ...
0
votes
1answer
34 views

Is the Bilateral Filter a Solution of Some Variational Method?

I've been watching these video lectures about variational methods in computer vision. In one of such video lectures a it is explained for example that the Gaussian filtering is a solution of the ...
0
votes
1answer
131 views

Intuitive Meaning of Regularization in Imaging Inverse Problems

Hello Every one I have been trying to understand the intuitive meaning of using a regularizer in images. Specifically what does the Total Variation regularizer do in images and how is it able to ...
0
votes
1answer
75 views

Total Variation of a Signal - Is It Proportional to Signal Energy?

In an audio application, I found it very useful to measure the total variation of a signal $y[n]$ $$\sum_{n=n_0}^{n_0+N} |y[n]-y[n-1]|$$ over a window of time length $N$ (discrete analogous to total ...
0
votes
1answer
89 views

TV Norm - What Would Be the Formula?

I have a 2-D discrete signal in which each point can be represented as $(x, y)$. These points are varying with time $t$. Can we represent the TV-norm using the following formula? $$\sum_{t}|x_t - x_{...
3
votes
1answer
324 views

How Can I Use MATLAB to Solve a Total Variation Denoising Problem?

The Total Variation Denoising Problem is given by: $$ \arg \min_{x} \frac{1}{2} {\left\| A x - y \right\|}_{2}^{2} + \lambda \operatorname{TV} \left( x \right) $$ Where $ $ is the Total Variation ...
2
votes
2answers
982 views

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

In this link, it says that the gradient is as follow The Gradient of the TV norm is $$ \mathrm{Grad}J(f)=\mathrm{div}\left(\frac{\nabla f}{\lVert\nabla f\rVert}\right). $$ From this other link, ...
0
votes
1answer
98 views

What Is the Difference Between MRF and Total Variation in Noise Removal?

I have a general question in image processing. I have a noisy image. I would like to classify the noisy image into some regions. Two famous approaches I can use are: MRF/Gibbs MRF: Model the spatial ...
3
votes
1answer
7k views

How to Calculate Total Variation (TV) of an Image?

TV is L1 norm of gradient of an image. So we've to find gradient of the image (which is still matrix, right?). Then take the sum of absolute values of the gradient matrix (So now it must be a scalar, ...
4
votes
3answers
2k views

Using Total Variation Denoising to Clean Accelerometer Data

I know this is maybe a very basic question but I am doing this as a hobby and I can't find a solution to this problem. Basically I am trying to remove some noise from data I am reading from an ...
6
votes
1answer
829 views

Gradient of Total Variation of Magnitude of Complex Function for Denoising

Say I have a complex function $f^*$ (e.g. a MRI image) that has a near piece-wise constant magnitude, but a non constant phase. If I have an optimization problem to find $f^*$ and set up an objective ...
19
votes
4answers
3k views

Bag of Tricks for Denoising Signals While Maintaining Sharp Transitions

I know this is signal dependent, but when facing a new noisy signal what is your bag of tricks for trying to denoise a signal while maintaining sharp transitions (e.g. so any sort of simple averaging, ...
10
votes
1answer
863 views

Image Denoising with Better Edge Preservation

I have the input image : and the output of vein detection for the leaf using a Gabor filter, but the output is really noisy: I tried using Total variation denoising however the results are not good: ...