add all scripts/tools

1 files changed, 32 insertions, 0 deletions

diff --git a/julia/calc_k_percentile.jl b/julia/calc_k_percentile.jl
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+++ b/julia/calc_k_percentile.jl
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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
+