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## Radially averaged power spectrum of 2D real-valued matrix

version 1.5 (2.09 KB) by

Computes and plots radially averaged PSD of 2-D real matrix with a given spatial resolution.

Updated

The radially averaged power spectrum (RAPS) is the direction-independent mean spectrum, i.e. the average of all possible directional power spectra. The radially averaged power spectrum provides a convenient means to view and compare information contained in 2-D spectra in 1-D. This function computes and plots the RAPS of an input matrix (does not consider corner values outside averaging radius). The image can be rectangular but must be 2-D (e.g., multi-color channel data is not supported). The spatial resolution of the data is also specified.

gianrocco lazzari

edo prasetyo

f e

Thanks

Amos

Jim Kasson

Joao Marcos

### Joao Marcos (view profile)

Also, even my region is ~1000km the spectrum shows energy up to 5000km...

Joao Marcos

### Joao Marcos (view profile)

Thank you for the file, it was very usefull.
I runned a test where I linearly interpolate a 50km wind data to 5km. I would expect a drop in the energy at 100km, but the spectra shows eenrgy cascating down to the 5km scale. Do you know why this happens?
Thank you

fong

### fong (view profile)

useful for understanding RAPSD to analysis the spectral characteristics of a halftone pattern?

Angjelina Protik

### Angjelina Protik (view profile)

for r = 0:floor(dimMax/2)
i{r + 1} = find(rho == r);
end
Pf = zeros(1, floor(dimMax/2)+1);
for r = 0:floor(dimMax/2)
Pf(1, r + 1) = nanmean( imgfp( i{r+1} ) );
end
there is some bug in this part

Stefano

### Stefano (view profile)

Hi, I found this to be faster, hope it helps, S.
%% code for fast radial averaging:
[xx,yy]=meshgrid(-1000:1000,-1000:1000);
rr=sqrt(xx.^2+yy.^2);
ri=floor(rr/100)+1;
N=numel(ri);
[~,~,iir]=unique(ri); %find unique values
Qt =sparse(1:N,iir,ones(N,1));