OpenCV利用查找表（Look-up table）增加图像对比度

#include "Histogram.h" #include <iostream> cv::MatND Histogram::getHistogram(const cv::Mat &image) { cv::MatND hist; cv::calcHist(&image, //看一下函数声明就会明白参数的意思 1, // histogram of 1 image only channels, // the channel used cv::Mat(), // no mask is used hist, // the resulting histogram 1, // it is a 1D histogram histSize, // number of bins ranges // pixel value range ); return hist; } cv::Mat Histogram::getHisotgramImage(const cv::Mat &image) { //得到图像的信道数 int channels = image.channels(); //将直方图最大值缩小为灰度级数的90% int hpt = static_cast<int>(0.9*histSize[0]); //初始化直方图矩阵,注意这里的画布一定要是三基色，要不然画不了彩色的line cv::Mat histImg(histSize[0]*channels, histSize[0], CV_8UC3, cv::Scalar(255,255,255)); std::vector<cv::Mat> images; std::vector<cv::Scalar> scalars; //如果是1通道图像则直方图是灰色 if(channels == 1) scalars.push_back(CV_RGB(0,0,0)); else { //注意Scalar的顺序是BGR scalars.push_back(CV_RGB(0,0,255)); scalars.push_back(CV_RGB(0,255,0)); scalars.push_back(CV_RGB(255,0,0)); } double minVal = 0; double maxVal = 0; //将通道分离，逐个求直方图 cv::split(image, images); for(int c=0; c<channels; c++) { cv::MatND hist = getHistogram(images[c]); //得到直方图的最大值和最小值和位置，以便对直方图缩放 cv::minMaxLoc(hist, &minVal, &maxVal, 0, 0); // std::cout<<scalars[c]<<std::endl; for(int h=0; h<histSize[0]; h++) { float binVal = hist.at<float>(h); int intensity = static_cast<int>(binVal*hpt/maxVal); //在histImg中画直线,要注意图像的坐标系 cv::line(histImg, cv::Point(h, histSize[0]*(c+1)), cv::Point(h,histSize[0]*(c+1)- intensity),scalars[c]); } } return histImg; } cv::Mat Histogram::creatLookupTable1(const cv::Mat &image, int minValue) { cv::MatND hist= getHistogram(image); int minBin, i; for (minBin=0; minBin<histSize[0]; minBin++) { if(hist.at<float>(minBin) > minValue) break; } int maxBin; for(maxBin = histSize[0] -1; maxBin >= 0; maxBin--) { if (hist.at<float>(maxBin) > minValue) break; } cv::Mat lookupTable(1, histSize[0], CV_8U); for( i = 0; i<histSize[0]; i++) { if (i<=minBin) lookupTable.at<uchar>(i) = 0; else if (minBin < i && i < maxBin) lookupTable.at<uchar>(i) = static_cast<uchar> (255.0*(i-minBin)/(maxBin - minBin)+0.5); else lookupTable.at<uchar>(i) = 255; } return lookupTable; } cv::Mat Histogram::creatLookupTable2(const cv::Mat &image) { int i; cv::Mat lookupTable(1, histSize[0], CV_8U); for( i = 0; i<histSize[0]; i++) { lookupTable.at<uchar>(i) = 255-i; } return lookupTable; } cv::Mat Histogram::applyLookupTable(const cv::Mat &image, const cv::Mat &lookupTable) { cv::Mat result; cv::LUT(image, lookupTable, result); return result; }