/
simple_color_balance.cpp
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/
simple_color_balance.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include <algorithm>
#include <iostream>
#include <vector>
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/xphoto.hpp"
namespace cv
{
namespace xphoto
{
template <typename T>
void balanceWhiteSimple(std::vector<Mat_<T> > &src, Mat &dst, const float inputMin, const float inputMax,
const float outputMin, const float outputMax, const float p)
{
/********************* Simple white balance *********************/
const float s1 = p; // low quantile
const float s2 = p; // high quantile
int nElements = src[0].depth() == CV_8U ? 256 : 4096;
float minValue0 = inputMin;
float maxValue0 = inputMax;
// deal with cv::calcHist (exclusive upper bound)
if (src[0].depth() == CV_32F || src[0].depth() == CV_64F) // floating
{
maxValue0 += MIN((inputMax - inputMin) / (nElements - 1), 1);
if (inputMax == inputMin) // single value
maxValue0 += 1;
}
else // integer
{
maxValue0 += 1;
}
float interval = (maxValue0 - minValue0) / float(nElements);
for (size_t i = 0; i < src.size(); ++i)
{
float minValue = minValue0;
float maxValue = maxValue0;
Mat img = src[i].reshape(1);
Mat hist;
int channels[] = {0};
int histSize[] = {nElements};
float inputRange[] = {minValue, maxValue};
const float *ranges[] = {inputRange};
calcHist(&img, 1, channels, Mat(), hist, 1, histSize, ranges, true, false);
int total = int(src[i].total());
int p1 = 0, p2 = nElements - 1;
int n1 = 0, n2 = total;
// searching for s1 and s2
while (n1 + hist.at<float>(p1) < s1 * total / 100.0f)
{
n1 += saturate_cast<int>(hist.at<float>(p1++));
minValue += interval;
}
while (n2 - hist.at<float>(p2) > (100.0f - s2) * total / 100.0f)
{
n2 -= saturate_cast<int>(hist.at<float>(p2--));
maxValue -= interval;
}
src[i] = (outputMax - outputMin) * (src[i] - minValue) / (maxValue - minValue) + outputMin;
}
/****************************************************************/
dst.create(/**/ src[0].size(), CV_MAKETYPE(src[0].depth(), int(src.size())) /**/);
cv::merge(src, dst);
}
class SimpleWBImpl CV_FINAL : public SimpleWB
{
private:
float inputMin, inputMax, outputMin, outputMax, p;
public:
SimpleWBImpl()
{
inputMin = 0.0f;
inputMax = 255.0f;
outputMin = 0.0f;
outputMax = 255.0f;
p = 2.0f;
}
float getInputMin() const CV_OVERRIDE { return inputMin; }
void setInputMin(float val) CV_OVERRIDE { inputMin = val; }
float getInputMax() const CV_OVERRIDE { return inputMax; }
void setInputMax(float val) CV_OVERRIDE { inputMax = val; }
float getOutputMin() const CV_OVERRIDE { return outputMin; }
void setOutputMin(float val) CV_OVERRIDE { outputMin = val; }
float getOutputMax() const CV_OVERRIDE { return outputMax; }
void setOutputMax(float val) CV_OVERRIDE { outputMax = val; }
float getP() const CV_OVERRIDE { return p; }
void setP(float val) CV_OVERRIDE { p = val; }
void balanceWhite(InputArray _src, OutputArray _dst) CV_OVERRIDE
{
CV_Assert(!_src.empty());
CV_Assert(_src.depth() == CV_8U || _src.depth() == CV_16S || _src.depth() == CV_32S || _src.depth() == CV_32F);
Mat src = _src.getMat();
Mat &dst = _dst.getMatRef();
switch (src.depth())
{
case CV_8U:
{
std::vector<Mat_<uchar> > mv;
split(src, mv);
balanceWhiteSimple(mv, dst, inputMin, inputMax, outputMin, outputMax, p);
break;
}
case CV_16S:
{
std::vector<Mat_<short> > mv;
split(src, mv);
balanceWhiteSimple(mv, dst, inputMin, inputMax, outputMin, outputMax, p);
break;
}
case CV_32S:
{
std::vector<Mat_<int> > mv;
split(src, mv);
balanceWhiteSimple(mv, dst, inputMin, inputMax, outputMin, outputMax, p);
break;
}
case CV_32F:
{
std::vector<Mat_<float> > mv;
split(src, mv);
balanceWhiteSimple(mv, dst, inputMin, inputMax, outputMin, outputMax, p);
break;
}
}
}
};
Ptr<SimpleWB> createSimpleWB() { return makePtr<SimpleWBImpl>(); }
}
}