Is Multifractal Analysis the Key to Removing Clutter in Radar Images?

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The discussion centers on the application of continuous multifractal analysis in radar image processing to reduce clutter. A participant initially questions the validity of their findings, noting that their results yield f(α) = α for all examined q values, indicating a mono-fractal rather than a multifractal nature. They later confirm this conclusion through a related paper discussing Cantor sets. Another user seeks guidance on implementing multifractal analysis techniques, specifically regarding the double trace moment in their thesis work on radar images. The conversation highlights the challenges and confirmations in applying multifractal methods to radar data.
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Has anybody ever come across a dataset which does the following?

I use the continuous multifractal (method of moments) technique to derive for a range of q
\tau , \alpha , f(\alpha )

However I find that f(\alpha ) = \alpha for every value q being examined. Therefore there is strictly no hyperbola for the f(a) curve and the data is therefore can't be multifractal. Right?

Thanks in advance :smile:
 
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Never mind.

Found a paper which discusses the issue in relation to Cantor sets :)

Apparently it just means that it's mono-fractal and not multifractal. Which is what I thought, this paper just confirmed it.

Mods feel free to delete post if necessary.
 
multifractal analysis

Hi all,

I am preparing a thesis at the multifractal and fractal analysis of radar images, to automatically set and remove clutter. I came to develop programs telque boxcountig function and of codimension years .. but I stopped confused when is about to determine the double trace moment ..any idea or just signs from you make me be grateful.

Thanks in advance
 

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