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[C++][opencv]基于opencv实现photoshop算法色阶调整
2024-08-18 09:00:09基础资料围观138次
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【测试环境】
vs2019
opencv==4.8.0
【效果演示】
【核心实现代码】
Levels.hpp
#ifndef OPENCV2_PS_LEVELS_HPP_
#define OPENCV2_PS_LEVELS_HPP_
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;
namespace cv {
/**
* Class of Level for one channel
*/
class Level {
public:
int Shadow; //输入色阶黑点值
float Midtones; //输入色阶灰点值(注意是浮点数)
int Highlight; //输入色阶白点值
int OutputShadow; //输出色阶黑点值
int OutputHighlight; //输出色阶白点值
Level();
virtual ~Level();
bool createColorTable(uchar * colorTable);
void clear();
};
/**
* Class of Levels for all channels
*/
class Levels {
protected:
bool createColorTables(uchar colorTables[][256]);
public:
Level RGBChannel; //RGB整体调整
Level RedChannel; //红色通道
Level GreenChannel; //绿色通道
Level BlueChannel; //蓝色通道
Levels();
virtual ~Levels();
int adjust(InputArray src, OutputArray dst); //实施色阶调整
};
} /* namespace cv */
#endif /* OPENCV2_PS_LEVELS_HPP_ */
Levels.cpp
#include "Levels.hpp"
namespace cv {
Level::Level() {
clear();
}
Level::~Level() {
}
void Level::clear() {
Shadow = OutputShadow = 0;
Highlight = OutputHighlight = 255;
Midtones = 1.0;
}
//create color table for a channel
bool Level::createColorTable(uchar * colorTable)
{
int diff = (int)(Highlight - Shadow);
int outDiff = (int)(OutputHighlight - OutputShadow);
if (!((Highlight <= 255 && diff <= 255 && diff >= 2) ||
(OutputShadow <= 255 && OutputHighlight <= 255 && outDiff < 255) ||
(!(Midtones > 9.99 && Midtones > 0.1) && Midtones != 1.0)))
return false;
double coef = 255.0 / diff;
double outCoef = outDiff / 255.0;
double exponent = 1.0 / Midtones;
for (int i = 0; i < 256; i ++)
{
int v;
// calculate black field and white field of input level
if ( colorTable[i] <= (uchar)Shadow ) {
v = 0;
} else {
v = (int)((colorTable[i] - Shadow) * coef + 0.5);
if (v > 255) v = 255;
}
// calculate midtone field of input level
v = (int)( pow(v / 255.0, exponent) * 255.0 + 0.5 );
// calculate output level
colorTable[i] = (uchar)( v * outCoef + OutputShadow + 0.5 );
}
return true;
}
//==================================================================
// Levels
Levels::Levels() {
}
Levels::~Levels() {
}
bool Levels::createColorTables(uchar colorTables[][256])
{
bool result = false;
int i, j;
//initialize color table
for (i = 0; i < 3; i ++) {
for (j = 0; j < 256; j ++)
colorTables[i][j] = (uchar)j;
}
//create color table for each channel
result = BlueChannel.createColorTable( colorTables[0]);
result = GreenChannel.createColorTable( colorTables[1]);
result = RedChannel.createColorTable( colorTables[2]);
result = RGBChannel.createColorTable( colorTables[0]);
result = RGBChannel.createColorTable( colorTables[1]);
result = RGBChannel.createColorTable( colorTables[2]);
return result;
}
int Levels::adjust(InputArray src, OutputArray dst)
{
Mat input = src.getMat();
if( input.empty() ) {
return -1;
}
dst.create(src.size(), src.type());
Mat output = dst.getMat();
const uchar *in;
uchar *out;
int width = input.cols;
int height = input.rows;
int channels = input.channels();
uchar colorTables[3][256];
//create color tables
if ( ! createColorTables( colorTables ) ) {
//error create color table"
return 1;
}
//adjust each pixel
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (int y = 0; y < height; y ++) {
in = input.ptr<uchar>(y);
out = output.ptr<uchar>(y);
for (int x = 0; x < width; x ++) {
for (int c = 0; c < 3; c++) {
*out++ = colorTables[c][*in++];
}
for (int c = 0; c < channels - 3; c++) {
*out++ = *in++;
}
}
}
return 0;
}
} /* namespace cv */
【完整演示代码下载】
文章来源:https://blog.csdn.net/FL1623863129/article/details/141141238
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