本文主要介紹了OpenCV 圖像對(duì)比度，具有一定的參考價(jià)值，感興趣的可以了解一下
實(shí)現(xiàn)原理
圖像對(duì)比度指的是一幅圖像中明暗區(qū)域最亮的白和最暗的黑之間不同亮度層級(jí)的測(cè)量，即指一幅圖像灰度反差的大小。差異范圍越大代表對(duì)比越大，差異范圍越小代表對(duì)比越小。設(shè)置一個(gè)基準(zhǔn)值thresh，當(dāng)percent大于0時(shí)，需要令圖像中的顏色對(duì)比更強(qiáng)烈，即數(shù)值距離thresh越遠(yuǎn)，則變化越大；當(dāng)percent等于1時(shí)，對(duì)比強(qiáng)到極致，只有255和0的區(qū)分；當(dāng)percent等于0時(shí)，不變；當(dāng)percent小于0時(shí)，對(duì)比下降，即令遠(yuǎn)離thresh的數(shù)值更近些；當(dāng)percent等于-1時(shí)，沒有對(duì)比了，全是thresh值。
對(duì)比度調(diào)整算法的實(shí)現(xiàn)流程如下：
1.設(shè)置調(diào)整參數(shù)percent，取值為-100到100，類似PS中設(shè)置，歸一化后為-1到1。
2.針對(duì)圖像所有像素點(diǎn)單個(gè)處理。當(dāng)percent大于等于0時(shí)，對(duì)比增強(qiáng)，調(diào)整后的RGB三通道數(shù)值為：
3.若percent小于0時(shí)，對(duì)比降低，此時(shí)調(diào)整后的圖像RGB三通道值為：
4.若percent等于1時(shí)，大于thresh則等于255，小于則等于0。
至此，圖像實(shí)現(xiàn)了明度的調(diào)整，算法邏輯參考xingyanxiao。C++實(shí)現(xiàn)代碼如下。
功能函數(shù)代碼
// 對(duì)比度
cv::Mat Contrast(cv::Mat src, int percent)
{
float alpha = percent / 100.f;
alpha = max(-1.f, min(1.f, alpha));
cv::Mat temp = src.clone();
int row = src.rows;
int col = src.cols;
int thresh = 127;
for (int i = 0; i row; ++i)
{
uchar *t = temp.ptruchar>(i);
uchar *s = src.ptruchar>(i);
for (int j = 0; j col; ++j)
{
uchar b = s[3 * j];
uchar g = s[3 * j + 1];
uchar r = s[3 * j + 2];
int newb, newg, newr;
if (alpha == 1)
{
t[3 * j + 2] = r > thresh ? 255 : 0;
t[3 * j + 1] = g > thresh ? 255 : 0;
t[3 * j] = b > thresh ? 255 : 0;
continue;
}
else if (alpha >= 0)
{
newr = static_castint>(thresh + (r - thresh) / (1 - alpha));
newg = static_castint>(thresh + (g - thresh) / (1 - alpha));
newb = static_castint>(thresh + (b - thresh) / (1 - alpha));
}
else {
newr = static_castint>(thresh + (r - thresh) * (1 + alpha));
newg = static_castint>(thresh + (g - thresh) * (1 + alpha));
newb = static_castint>(thresh + (b - thresh) * (1 + alpha));
}
newr = max(0, min(255, newr));
newg = max(0, min(255, newg));
newb = max(0, min(255, newb));
t[3 * j + 2] = static_castuchar>(newr);
t[3 * j + 1] = static_castuchar>(newg);
t[3 * j] = static_castuchar>(newb);
}
}
return temp;
}
C++測(cè)試代碼
#include opencv2/opencv.hpp>
#include iostream>
using namespace cv;
using namespace std;
cv::Mat Contrast(cv::Mat src, int percent);
int main()
{
cv::Mat src = imread("5.jpg");
cv::Mat result = Contrast(src, 50.f);
imshow("original", src);
imshow("result", result);
waitKey(0);
return 0;
}
// 對(duì)比度
cv::Mat Contrast(cv::Mat src, int percent)
{
float alpha = percent / 100.f;
alpha = max(-1.f, min(1.f, alpha));
cv::Mat temp = src.clone();
int row = src.rows;
int col = src.cols;
int thresh = 127;
for (int i = 0; i row; ++i)
{
uchar *t = temp.ptruchar>(i);
uchar *s = src.ptruchar>(i);
for (int j = 0; j col; ++j)
{
uchar b = s[3 * j];
uchar g = s[3 * j + 1];
uchar r = s[3 * j + 2];
int newb, newg, newr;
if (alpha == 1)
{
t[3 * j + 2] = r > thresh ? 255 : 0;
t[3 * j + 1] = g > thresh ? 255 : 0;
t[3 * j] = b > thresh ? 255 : 0;
continue;
}
else if (alpha >= 0)
{
newr = static_castint>(thresh + (r - thresh) / (1 - alpha));
newg = static_castint>(thresh + (g - thresh) / (1 - alpha));
newb = static_castint>(thresh + (b - thresh) / (1 - alpha));
}
else {
newr = static_castint>(thresh + (r - thresh) * (1 + alpha));
newg = static_castint>(thresh + (g - thresh) * (1 + alpha));
newb = static_castint>(thresh + (b - thresh) * (1 + alpha));
}
newr = max(0, min(255, newr));
newg = max(0, min(255, newg));
newb = max(0, min(255, newb));
t[3 * j + 2] = static_castuchar>(newr);
t[3 * j + 1] = static_castuchar>(newg);
t[3 * j] = static_castuchar>(newb);
}
}
return temp;
}
測(cè)試效果
圖1 原圖
圖2 參數(shù)為50的效果圖
圖3 參數(shù)為-50的效果圖
通過調(diào)整percent可以實(shí)現(xiàn)圖像對(duì)比度的調(diào)整。
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