1. 参考文献：

Visual Attention Detection in Video Sequences Using Spatiotemporal Cues。 Yun Zhai and Mubarak Shah.  Page 4-5

2. 模型实现

2.1 显著性检测公共头文件

#ifndef SALIENTCOMMON_H
#define SALIENTCOMMON_H
// std lib
#include <iostream>
#include <string>
#include <vector>
#include <fstream>// opencv lib
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/imgcodecs/imgcodecs.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/ml/ml.hpp>using namespace std;
using namespace cv;#endif // SALIENTCOMMON_H

2.2 显著性检测头文件

#ifndef SALIENTLC_H
#define SALIENTLC_H
#include "salientcommon.h"
// 参考论文：Visual Attention Detection in Video Sequences Using Spatiotemporal Cues。 Yun Zhai and Mubarak Shah.  Page 4-5
//
class salientLC
{
public:salientLC(Mat orgImg);~salientLC();void m_getSalientLC(Mat& resultImg);
private:void m_getHistgram();void m_Normalize(Mat& distMap);void m_rgb2Lab();void m_getDistTable();
private:Mat m_orgImg;Mat m_labImg;unsigned int m_maxDist;unsigned int m_minDist;unsigned int m_hist[256];unsigned int m_distTable[256];Mat m_resultImg;
};#endif // SALIENTLC_H

2.3 显著性检测实现文件(.cpp)

#include "salientlc.h"salientLC::salientLC(Mat orgImg)
{orgImg.copyTo(m_orgImg);m_minDist = (unsigned int)0xEFFFFFFF;m_maxDist = (unsigned int)0x00000000;memset(m_hist, 0, sizeof(m_hist));memset(m_distTable, 0, sizeof(m_distTable));m_rgb2Lab();m_getDistTable();
}salientLC::~salientLC()
{;
}void salientLC::m_getSalientLC(Mat& resultImg)
{int W = m_labImg.cols;int H = m_labImg.rows;int rowIter, colIter;unsigned int histIter;int channelIter;Mat distMap = Mat::zeros(Size(W,H), CV_32FC1);m_getHistgram();for(rowIter = 0; rowIter < H; ++rowIter){for(colIter = 0; colIter < W; ++colIter){unsigned int tmpVal = 0;for(channelIter = 0; channelIter < 3; ++channelIter){unsigned int  value = m_labImg.at<Vec3b>(rowIter, colIter)[channelIter];for(histIter = 0; histIter < 256; ++histIter){int absVal = histIter > value ? histIter - value : value - histIter;tmpVal += m_hist[histIter] * m_distTable[absVal];}}distMap.at<float>(rowIter, colIter)  =  tmpVal;if(distMap.at<float>(rowIter, colIter) < m_minDist){m_minDist = distMap.at<float>(rowIter, colIter);}if(distMap.at<float>(rowIter, colIter) > m_maxDist){m_maxDist = distMap.at<float>(rowIter, colIter);}}}cout << "minDist = " << m_minDist << ", " << "maxDist = " << m_maxDist << endl;m_Normalize(distMap);m_resultImg.copyTo(resultImg);
}void salientLC::m_getHistgram()
{int W = m_labImg.cols;int H = m_labImg.rows;int rowIter, colIter;for(rowIter = 0; rowIter < H; ++rowIter){for(colIter = 0; colIter < W; ++colIter){m_hist[m_labImg.at<uchar>(rowIter, colIter)]++;}}
}void salientLC::m_getDistTable()
{int iter;for(iter = 0; iter < 256; ++iter){m_distTable[iter] = iter * iter;}
}void salientLC::m_Normalize(Mat& distMap)
{int W = distMap.cols;int H = distMap.rows;int rowIter, colIter;m_resultImg = Mat::zeros(Size(W,H), CV_8UC1);for(rowIter = 0; rowIter < H; ++rowIter){for(colIter = 0; colIter < W; ++colIter){m_resultImg.at<uchar>(rowIter,colIter) = (int)((distMap.at<float>(rowIter, colIter)  - m_minDist)* 1.0 / (m_maxDist - m_minDist) * 255);}}
}void salientLC::m_rgb2Lab()
{Mat tmpImg;if(m_orgImg.channels() == 1){cvtColor(m_orgImg, tmpImg, CV_GRAY2BGR);}else{m_orgImg.copyTo(tmpImg);}cvtColor(tmpImg, m_labImg, CV_BGR2Lab);
}

3. 实现效果：