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# -*- coding: utf-8 -*-
#
# Calculate the percentile of the gradient image, which
# used as the 'kappa' parameter of the anisotropic diffusion.
#
# Credits:
# [1] KAZE: nldiffusion_functions.cpp / compute_k_percentile()
#
# Aaron LI
# 2015/07/20
#
include("scharr.jl");
function calc_k_percentile(img, percent=0.7, nbins=300)
rows, cols = size(img)
# derivatives of the image
img_gx = scharr(img, 1, 0)
img_gy = scharr(img, 0, 1)
img_modg = sqrt(img_gx.^2 + img_gy.^2)
# histogram
hmax = maximum(img_modg)
hist_e, hist_counts = hist(reshape(img_modg, length(img_modg)), nbins)
hist_cum = cumsum(hist_counts)
# find the percent of the histogram percentile
npoints = sum(img_modg .> 0.0)
nthreshold = npoints * percent
k = sum(hist_cum .<= nthreshold)
kperc = (k == length(hist_cum)) ? 0.03 : (hmax * k / nbins)
return kperc
end
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