From c9c896dea2ba43551c4e10bd49666105449e9bd7 Mon Sep 17 00:00:00 2001
From: Aaron LI <aaronly.me@gmail.com>
Date: Thu, 31 Mar 2016 10:57:34 +0800
Subject: add all scripts/tools

---
 julia/calc_k_percentile.jl | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 julia/calc_k_percentile.jl

(limited to 'julia/calc_k_percentile.jl')

diff --git a/julia/calc_k_percentile.jl b/julia/calc_k_percentile.jl
new file mode 100644
index 0000000..36b15e1
--- /dev/null
+++ b/julia/calc_k_percentile.jl
@@ -0,0 +1,32 @@
+# -*- 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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