6
votes
How to decide whether a recording contains a signal of interest?
Is it possible to decide based on the result of the cross-correlation whether a recording contains the signal of interest?
Certainly. The easiest way would be look at the crest factor (peak to RMS ...
- 48.2k
6
votes
Detect valleys of a signal
First, you'll probably have better luck posting this on dsp.stackexchange. That's a more specialized group that does stuff like this all the time.
In terms of your problem, here's a couple of ...
- 309
3
votes
Optimal Level of Wavelet Decomposition for Denoising
Best denoising should be related to certain quality measures, often requiring the clean signal reference, which you do not have in general. Or you could rely on some reference-free measures.
To the ...
- 32.3k
3
votes
Accepted
In Plain English, What Are the Within and Between Class Variances in Otsu's Thresholding?
i'm avoiding labels light and dark because you could say that we choose 128 as threshold which perfectly separate light and dark pixels but consider you have a picture with only two gray levels which ...
- 1,417
3
votes
Best way of segmenting veins in leaves?
This topic has always attracted a lot of interest, and yet no real consensus exists on the topic. Therefore I decided to drop a few words.
My answers to previously asked similar questions on ...
- 5,515
2
votes
Double Threshold Mechanism
It is possible that it refers to hysteresis thresholding. This is where the image is thresholded twice, at a low threshold and a high one. The connected components of the low threshold that contain at ...
- 2,770
2
votes
Threshold for peak detection of noisy signal in frequency domain
This is a pretty common problem in radar signal processing. Typically, we’ll use what’s called a CFAR detector (constant false alarm rate). This essentially boils down to a non-linear smoothing filter ...
- 863
2
votes
Good way for segmenting this signal
I solved this by still using Otsu to find the threshold value. I then just filter the the regions with value == 1 in the thresholded signal (i.e. the ...
- 275
2
votes
How to decide whether a recording contains a signal of interest?
Have you tried setting a threshold based on the signal statistics?
For your first approach (could be applied to your second as well, only in the frequency domain), that would look something like:
<...
- 6,814
2
votes
Accepted
Finding optimal decision threshold for binary comm system
Let P(0) ( P(1) ) is a probability of transmitting bit zero (one); P(e|0) ( P(e|1) ) is a probability of error when detecting bit zero (one).
The probability of erroneous detection is
$$
P(e) = P(e|0)...
- 1,774
1
vote
Accepted
Concept of energy threshold
Does the "Energy Threshold" carry information about the end of the noise and the beginning of the packet due to the calculated arithmetic mean?
There's no such thing as "end of noise&...
- 32.5k
1
vote
What are the possible ways to find spots with most concentrated contrast on an image?
Pass a sliding window of eg 100x100 pixels over the image stepped 1 pixel at a time in each dimension. Note the maximum and the minimum pixel value. The local contrast is now the local_max/local_min.
...
- 3,595
1
vote
How to determine a suitable threshold when using amplitude thresholding method for spike detection?
For threshold-based spike detection, the threshold defines your performance in the detection vs false alarm performance. That is to say, a lower threshold will improve your probability of detecting (...
- 2,463
1
vote
Signal analysis: selection of oscillatory parts
Take a morlet wavelet and run it over the entire signal. The frequency in the morlet wavelet can be set close to the frequency of these transitory regions. Even if not close to frequency of transition ...
- 2,655
1
vote
Accepted
Signal analysis: selection of oscillatory parts
By looking at that graph, it seems that simple math (or rather statistics) can be used to solve this problem. I'd divide (segment) your data into equal time frames and then compute the mean and ...
- 931
1
vote
How to discard deviating values from standard deviation and running average
Let's ignore the issue that you already have a discrimination problem in your hands (bus/car/truck/van) there is an initial discrimination problem that has to be solved for the data to be considered ...
- 157
1
vote
Threshold for peak detection of noisy signal in frequency domain
Look for peaks N dB above the localized noise floor.
Calculate the noise floor by taking the mean of all your samples (or choose an observation window size). You can throw out the top 1-3 samples (...
- 541
1
vote
Detect valleys of a signal
I did not read carefully through the whole question as I don't have time now, but have you tried some form of robust peak detection? See e.g., https://docs.scipy.org/doc/scipy/reference/generated/...
- 85
1
vote
Binarization, and then thinning/skeletonization
Your implementation of the ZS algorithm is wrong. The correct output should be:
Here you can see the output superimposed on the original binary image:
Removing the small branches would require a ...
- 236
1
vote
Is document image binarization a closed research field
First, in science, a field is rarely closed, sometimes asleep only. Resistance to low-contrast, real-time, badly scanned, composite documents/writers or from aging medium seem to remain challenges, ...
- 32.3k
1
vote
select local maxima in energy signal
I would suggest you apply a median filter, e.g.,
y=filter(1,0.05*ones(1,20),x)
And then apply Matlab function findpeaks. As an ...
- 761
1
vote
Optimal Level of Wavelet Decomposition for Denoising
I'd say it depends on the noise properties and of course the image itself.
What you can think is that most Denoise Filters can handle only the High Frequencies of the noise.
Hence the decomposition ...
- 20.5k
1
vote
Motion detection one threshold over dataset
I could suggest several things. I am not sure if you already try them and I am not sure of the requirements either. Assuming that you need real-time analysis and performances:
What about normalizing ...
- 311
1
vote
What are the various techniques for detecting walls in buildings (architectural) in floor plan images?
Try using Template matching by taking a small cutout of the wall whose length is long enough so that it is not confused with other elements. Keep the threshold value high(around 0.9 or higher) and ...
- 11
1
vote
Denoising by DCT and hard thresholding
DCTs are very useful at energy compaction, so simply put after a DCT of an image is resolved to a weighted some of some basis functions. After a DCT, the resulting matrix will contains multipliers for ...
- 111
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