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median_cut.h
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// Aseprite Render Library
// Copyright (c) 2001-2017 David Capello
//
// This file is released under the terms of the MIT license.
// Read LICENSE.txt for more information.
#ifndef RENDER_MEDIAN_CUT_H_INCLUDED
#define RENDER_MEDIAN_CUT_H_INCLUDED
#pragma once
#include "doc/color.h"
#include <list>
#include <queue>
namespace render {
template<class Histogram>
class Box {
// These classes are used as parameters for some Box's generic
// member functions, so we can access to a different axis using
// the same generic function (i=Red channel in RAxisGetter, etc.).
struct RAxisGetter { static std::size_t at(const Histogram& h, int i, int j, int k, int l) { return h.at(i, j, k, l); } };
struct GAxisGetter { static std::size_t at(const Histogram& h, int i, int j, int k, int l) { return h.at(j, i, k, l); } };
struct BAxisGetter { static std::size_t at(const Histogram& h, int i, int j, int k, int l) { return h.at(j, k, i, l); } };
struct AAxisGetter { static std::size_t at(const Histogram& h, int i, int j, int k, int l) { return h.at(j, k, l, i); } };
// These classes are used as template parameter to split a Box
// along an axis (see splitAlongAxis)
struct RAxisSplitter {
static Box box1(const Box& box, int r) { return Box(box.r1, box.g1, box.b1, box.a1, r, box.g2, box.b2, box.a2); }
static Box box2(const Box& box, int r) { return Box(r, box.g1, box.b1, box.a1, box.r2, box.g2, box.b2, box.a2); }
};
struct GAxisSplitter {
static Box box1(const Box& box, int g) { return Box(box.r1, box.g1, box.b1, box.a1, box.r2, g, box.b2, box.a2); }
static Box box2(const Box& box, int g) { return Box(box.r1, g, box.b1, box.a1, box.r2, box.g2, box.b2, box.a2); }
};
struct BAxisSplitter {
static Box box1(const Box& box, int b) { return Box(box.r1, box.g1, box.b1, box.a1, box.r2, box.g2, b, box.a2); }
static Box box2(const Box& box, int b) { return Box(box.r1, box.g1, b, box.a1, box.r2, box.g2, box.b2, box.a2); }
};
struct AAxisSplitter {
static Box box1(const Box& box, int a) { return Box(box.r1, box.g1, box.b1, box.a1, box.r2, box.g2, box.b2, a ); }
static Box box2(const Box& box, int a) { return Box(box.r1, box.g1, box.b1, a, box.r2, box.g2, box.b2, box.a2); }
};
public:
Box(int r1, int g1, int b1, int a1,
int r2, int g2, int b2, int a2)
: r1(r1), g1(g1), b1(b1), a1(a1)
, r2(r2), g2(g2), b2(b2), a2(a2)
, points(0)
, volume(calculateVolume()) {
}
// Shrinks each plane of the box to a position where there are
// points in the histogram.
void shrink(const Histogram& histogram) {
axisShrink<RAxisGetter>(histogram, r1, r2, g1, g2, b1, b2, a1, a2);
axisShrink<GAxisGetter>(histogram, g1, g2, r1, r2, b1, b2, a1, a2);
axisShrink<BAxisGetter>(histogram, b1, b2, r1, r2, g1, g2, a1, a2);
axisShrink<AAxisGetter>(histogram, a1, a2, r1, r2, g1, g2, b1, b2);
// Calculate number of points inside the box (this is done by
// first time here, because the Box ctor didn't calculate it).
points = countPoints(histogram);
// Recalculate the volume (used in operator<).
volume = calculateVolume();
}
bool split(const Histogram& histogram, std::priority_queue<Box>& boxes) const {
// Split along the largest dimension of the box.
if ((r2-r1) >= (g2-g1) &&
(r2-r1) >= (b2-b1) &&
(r2-r1) >= (a2-a1)) {
return splitAlongAxis<RAxisGetter, RAxisSplitter>(histogram, boxes, r1, r2, g1, g2, b1, b2, a1, a2);
}
if ((g2-g1) >= (r2-r1) &&
(g2-g1) >= (b2-b1) &&
(g2-g1) >= (a2-a1)) {
return splitAlongAxis<GAxisGetter, GAxisSplitter>(histogram, boxes, g1, g2, r1, r2, b1, b2, a1, a2);
}
if ((b2-b1) >= (r2-r1) &&
(b2-b1) >= (g2-g1) &&
(b2-b1) >= (a2-a1)) {
return splitAlongAxis<BAxisGetter, BAxisSplitter>(histogram, boxes, b1, b2, r1, r2, g1, g2, a1, a2);
}
return splitAlongAxis<AAxisGetter, AAxisSplitter>(histogram, boxes, a1, a2, r1, r2, g1, g2, b1, b2);
}
// Returns the color enclosed by the box calculating the mean of
// all histogram's points inside the box.
uint32_t meanColor(const Histogram& histogram) const {
std::size_t r = 0, g = 0, b = 0, a = 0;
std::size_t count = 0;
int i, j, k, l;
for (i=r1; i<=r2; ++i)
for (j=g1; j<=g2; ++j)
for (k=b1; k<=b2; ++k)
for (l=a1; l<=a2; ++l) {
int c = histogram.at(i, j, k, l);
r += c * i;
g += c * j;
b += c * k;
a += c * l;
count += c;
}
// No colors in the box? This should not be possible.
ASSERT(count > 0 && "Box without histogram points, you must fill the histogram before using this function.");
if (count == 0)
return doc::rgba(0, 0, 0, 255);
// Calculate the mean. We have to do this before the *255
// multiplication to avoid a 32-bit overflow. E.g. Alpha channel
// is the most proper to overflow the 32-bit capacity in case
// all pixels are opaque.
r /= count;
g /= count;
b /= count;
a /= count;
return doc::rgba(int(255 * r / (Histogram::RElements-1)),
int(255 * g / (Histogram::GElements-1)),
int(255 * b / (Histogram::BElements-1)),
int(255 * a / (Histogram::AElements-1)));
}
// The boxes will be sort in the priority_queue by volume.
bool operator<(const Box& other) const {
return volume < other.volume;
}
private:
// Calculates the volume from the current box's dimensions. The
// value returned by this function is cached in the "volume"
// variable member of Box class to avoid multiplying several
// times.
int calculateVolume() const {
return (r2-r1+1) * (g2-g1+1) * (b2-b1+1) * (a2-a1+1);
}
// Returns the number of histogram's points inside the box bounds.
std::size_t countPoints(const Histogram& histogram) const {
std::size_t count = 0;
int i, j, k, l;
for (i=r1; i<=r2; ++i)
for (j=g1; j<=g2; ++j)
for (k=b1; k<=b2; ++k)
for (l=a1; l<=a2; ++l)
count += histogram.at(i, j, k, l);
return count;
}
// Reduces the specified side of the box (i1/i2) along the
// specified axis (if AxisGetter is RAxisGetter, then i1=r1,
// i2=r2; if AxisGetter is GAxisGetter, then i1=g1, i2=g2).
template<class AxisGetter>
static void axisShrink(const Histogram& histogram,
int& i1, int& i2,
const int& j1, const int& j2,
const int& k1, const int& k2,
const int& l1, const int& l2)
{
int j, k, l;
// Shrink i1.
for (; i1<i2; ++i1) {
for (j=j1; j<=j2; ++j) {
for (k=k1; k<=k2; ++k) {
for (l=l1; l<=l2; ++l) {
if (AxisGetter::at(histogram, i1, j, k, l) > 0)
goto doneA;
}
}
}
}
doneA:;
for (; i2>i1; --i2) {
for (j=j1; j<=j2; ++j) {
for (k=k1; k<=k2; ++k) {
for (l=l1; l<=l2; ++l) {
if (AxisGetter::at(histogram, i2, j, k, l) > 0)
goto doneB;
}
}
}
}
doneB:;
}
// Splits the box in two sub-boxes (if it's possible) along the
// specified axis by AxisGetter template parameter and "i1/i2"
// arguments. Returns true if the split was done and the "boxes"
// queue contains the new two sub-boxes resulting from the split
// operation.
template<class AxisGetter, class AxisSplitter>
bool splitAlongAxis(const Histogram& histogram,
std::priority_queue<Box>& boxes,
const int& i1, const int& i2,
const int& j1, const int& j2,
const int& k1, const int& k2,
const int& l1, const int& l2) const {
// These two variables will be used to count how many points are
// in each side of the box if we split it in "i" position.
std::size_t totalPoints1 = 0;
std::size_t totalPoints2 = this->points;
int i, j, k, l;
// We will try to split the box along the "i" axis. Imagine a
// plane which its normal vector is "i" axis, so we will try to
// move this plane from "i1" to "i2" to find the median, where
// the number of points in both sides of the plane are
// approximated the same.
for (i=i1; i<=i2; ++i) {
std::size_t planePoints = 0;
// We count all points in "i" plane.
for (j=j1; j<=j2; ++j)
for (k=k1; k<=k2; ++k)
for (l=l1; l<=l2; ++l)
planePoints += AxisGetter::at(histogram, i, j, k, l);
// As we move the plane to split through "i" axis One side is getting more points,
totalPoints1 += planePoints;
totalPoints2 -= planePoints;
if (totalPoints1 > totalPoints2) {
if (totalPoints2 > 0) {
Box box1(AxisSplitter::box1(*this, i));
Box box2(AxisSplitter::box2(*this, i+1));
box1.points = totalPoints1;
box2.points = totalPoints2;
boxes.push(box1);
boxes.push(box2);
return true;
}
else if (totalPoints1-planePoints > 0) {
Box box1(AxisSplitter::box1(*this, i-1));
Box box2(AxisSplitter::box2(*this, i));
box1.points = totalPoints1-planePoints;
box2.points = totalPoints2+planePoints;
boxes.push(box1);
boxes.push(box2);
return true;
}
else
return false;
}
}
return false;
}
int r1, g1, b1, a1; // Min point (closest to origin)
int r2, g2, b2, a2; // Max point
std::size_t points; // Number of points in the space which enclose this box
int volume;
}; // end of class Box
// Median Cut Algorithm as described in P. Heckbert, "Color image
// quantization for frame buffer display,", Computer Graphics,
// 16(3), pp. 297-307 (1982)
template<class Histogram>
void median_cut(const Histogram& histogram, std::size_t maxBoxes, std::vector<uint32_t>& result) {
// We need a priority queue to split bigger boxes first (see Box::operator<).
std::priority_queue<Box<Histogram> > boxes;
// First we start with one big box containing all histogram's samples.
boxes.push(Box<Histogram>(0, 0, 0, 0,
Histogram::RElements-1,
Histogram::GElements-1,
Histogram::BElements-1,
Histogram::AElements-1));
// Then we split each box until we reach the maximum specified by
// the user (maxBoxes) or until there aren't more boxes to split.
while (!boxes.empty() && boxes.size() < maxBoxes) {
// Get and remove the first (bigger) box to process from "boxes" queue.
Box<Histogram> box(boxes.top());
boxes.pop();
// Shrink the box to the minimum, to enclose the same points in
// the histogram.
box.shrink(histogram);
// Try to split the box along the largest axis.
if (!box.split(histogram, boxes)) {
// If we were not able to split the box (maybe because it is
// too small or there are not enough points to split it), then
// we add the box's color to the "result" vector directly (the
// box is not in the queue anymore).
if (result.size() < maxBoxes)
result.push_back(box.meanColor(histogram));
else
return;
}
}
// When we reach the maximum number of boxes, we convert each box
// to a color for the "result" vector.
while (!boxes.empty() && result.size() < maxBoxes) {
const Box<Histogram>& box(boxes.top());
doc::color_t color = box.meanColor(histogram);
result.push_back(color);
boxes.pop();
}
}
} // namespace render
#endif