Finding Dominant Peaks and Valleys of an Image Histogram

This function finds dominant peaks and local valleys of an image histogram

This function finds dominant peaks and valleys of an image histogram. Minimum peak distance and averaging filter size can be changed to suit your need.
Although, the function is originally written for mages, there is no reason why this can't be used on one dimensional data.

USAGE:
[peaks minima_low minima_high] = findlocalminima(I,10,5,0);
OR
[peaks minima_low minima_high] = findlocalminima(I);

Example:
I = imread('cameraman.tif');
[peaks minima_low minima_high] = findlocalminima(I);

'minima_low' and 'minima_high' correspond to the local minimums beside each of the peak identified in 'peaks'

This is the function that is used for peak detection in my paper,
"De Silva, D.V.S.; Fernando, W.A.C.; Kodikaraarachchi, H.; Worrall, S.T.; Kondoz, A.M.; ,"Adaptive sharpening of depth maps for 3D-TV," Electronics Letters , vol.46, no.23, pp.1546 -1548, November 11 2010. Kindly consider to cite this paper if you use this in your work.