显著性检测代码及图片_显著性检测HC/LC/AC/FT算法_

#include "HC.h" using namespace std; template<typename T> inline T sqr(T x) { return x * x; } typedef vector<string> vecS; typedef vector<int> vecI; typedef vector<float> vecF; typedef vector<double> vecD; typedef pair<double, int> CostIdx; typedef pair<float, int> CostfIdx; template<class T> inline T vecDist3(const Vec<T, 3> &v1, const Vec<T, 3> &v2) { return sqrt(sqr(v1[0] - v2[0]) + sqr(v1[1] - v2[1]) + sqr(v1[2] - v2[2])); } template<class T> inline T vecSqrDist3(const Vec<T, 3> &v1, const Vec<T, 3> &v2) { return sqr(v1[0] - v2[0]) + sqr(v1[1] - v2[1]) + sqr(v1[2] - v2[2]); } /********************************* 函数声明：计算显著性图函数 参数：NONE 注释：NONE 测试： Mat srcImage, dstImage; srcImage = imread("0.jpg");//读取灰度图 imshow("原图",srcImage); HC hc; hc.calculateSaliencyMap(&srcImage, &dstImage); imshow("HC算法显著图", dstImage); waitKey(); return 0; **********************************/ void HC::calculateSaliencyMap(Mat *src, Mat * dst) { Mat img3f; (*src).convertTo(img3f, CV_32FC3, 1.0 / 255); //将原图像素值缩放1/255 Mat idx1i, binColor3f, colorNums1i, weight1f, _colorSal; Quantize(img3f, idx1i, binColor3f, colorNums1i);//颜色量化 cvtColor(binColor3f, binColor3f, COLOR_BGR2Lab); normalize(colorNums1i, weight1f, 1, 0, NORM_L1, CV_32F); GetHC(binColor3f, weight1f, _colorSal); float* colorSal = (float*)(_colorSal.data); Mat salHC1f(img3f.size(), CV_32F); for (int r = 0; r < img3f.rows; r++) { float* salV = salHC1f.ptr<float>(r); int* _idx = idx1i.ptr<int>(r); for (int c = 0; c < img3f.cols; c++) salV[c] = colorSal[_idx[c]]; } GaussianBlur(salHC1f, salHC1f, Size(3, 3), 0); normalize(salHC1f, *dst, 0, 1, NORM_MINMAX); } /********************************* 函数声明：量化颜色数量函数 参数： Mat& img3f: double ratio：找出像素数目覆盖图像不小于95%的高频颜色，以及其他的不高于5%的颜色种类 注释：NONE 测试：NONE **********************************/ int HC::Quantize(const Mat& img3f, Mat &idx1i, Mat &_color3f, Mat &_colorNum, double ratio ) { static const int clrNums[3] = { 12, 12, 12 }; static const float clrTmp[3] = { clrNums[0] - 0.0001f, clrNums[1] - 0.0001f, clrNums[2] - 0.0001f }; static const int w[3] = { clrNums[1] * clrNums[2], clrNums[2], 1 }; CV_Assert(img3f.data != NULL); idx1i = Mat::zeros(img3f.size(), CV_32S); int rows = img3f.rows, cols = img3f.cols; if (img3f.isContinuous() && idx1i.isContinuous()) //这里的continue的意思是在内存上continue，正常情况下，头一行的末尾在内存里和下一行的开头是相连的， //但是有时候我们做了一些操作，选取了Mat 的一部分，例如选了一个ROI 这时候就不满足上面说的相连了。那么这时候continuous就被判定为假。 { cols *= rows; rows = 1; } // 建立调色板 std::map<int, int> pallet; //map键值对 for (int y = 0; y < rows; y++)//遍历整个图像 { const float* imgData = img3f.ptr<float>(y); int* idx = idx1i.ptr<int>(y); for (int x = 0; x < cols; x++, imgData += 3) { idx[x] = (int)(imgData[0] * clrTmp[0])*w[0] + (int)(imgData[1] * clrTmp[1])*w[1] + (int)(imgData[2] * clrTmp[2]);//三个通道像素 pallet[idx[x]] ++; } } // Fine significant colors int maxNum = 0;//找出像素数目覆盖图像不小于95%的高频颜色，以及其他的不高于5%的颜色种类，假设高频颜色共有maxnum种 { int count = 0; vector<pair<int, int>> num; // (num, color) pairs in num num.reserve(pallet.size()); for (map<int, int>::iterator it = pallet.begin(); it != pallet.end(); it++) num.push_back(pair<int, int>(it->second, it->first)); // (color, num) pairs in pallet sort(num.begin(), num.end(), std::greater< pair<int, int> >()); maxNum = (int)num.size(); int maxDropNum = cvRound(rows * cols * (1 - ratio)); for (int crnt = num[maxNum - 1].first; crnt < maxDropNum && maxNum > 1; maxNum--) crnt += num[maxNum - 2].first; maxNum = min(maxNum, 256); // To avoid very rarely case if (maxNum < 10) maxNum = min((int)pallet.size(), 100); pallet.clear(); for (int i = 0; i < maxNum; i++) pallet[num[i].second] = i; vector<Vec3i> color3i(num.size()); for (unsigned int i = 0; i < num.size(); i++) { color3i[i][0] = num[i].second / w[0]; color3i[i][1] = num[i].second % w[0] / w[1]; color3i[i][2] = num[i].second % w[1]; } for (unsigned int i = maxNum; i < num.size(); i++) { int simIdx = 0, simVal = INT_MAX; for (int j = 0; j < maxNum; j++) { int d_ij = vecSqrDist3(color3i[i], color3i[j]); if (d_ij < simVal) simVal = d_ij, simIdx = j; } pallet[num[i].second] = pallet[num[simIdx].second]; } } _color3f = Mat::zeros(1, maxNum, CV_32FC3); _colorNum = Mat::zeros(_color3f.size(), CV_32S); Vec3f* color = (Vec3f*)(_color3f.data); int* colorNum = (int*)(_colorNum.data); for (int y = 0; y < rows; y++) { const Vec3f* imgData = img3f.ptr<Vec3f>(y); int* idx = idx1i.ptr<int>(y); for (int x = 0; x < cols; x++) { idx[x] = pallet[idx[x]]; color[idx[x]] += imgData[x]; colorNum[idx[x]] ++; } } for (int i = 0; i < _color3f.cols; i++) color[i] = color[i] / colorNum[i]; return _color3f.cols; } /********************************* 函数声明：计算显著图 参数：NONE 注释：NONE 测试：NONE **********************************/ void HC::GetHC(const Mat &binColor3f, const Mat &weight1f, Mat &_colorSal) { int binN = binColor3f.cols; _colorSal = Mat::zeros(1, binN, CV_32F); float* colorSal = (float*)(_colorSal.data); vector<vector< pair<double, int>>> similar(binN); // Similar color: how similar and their index Vec3f* color = (Vec3f*)(binColor3f.data); float *w = (float*)(weight1f.data); for (int i = 0; i < binN; i++) { vector< pair<double, int>> &similari = similar[i]; similari.push_back(make_pair(0.f, i)); for (int j = 0; j < binN; j++) { if (i == j) continue; float dij = vecDist3<float>(color[i], color[j]); similari.push_back(make_pair(dij, j)); colorSal[i] += w[j] * dij; } sort(similari.begin(), similari.end()); } SmoothSaliency(binColor3f, _colorSal, 4.0f, similar); } /********************************* 函数声明：平滑处理函数 参数：NONE 注释：NONE 测试：NONE **********************************/ void HC::SmoothSaliency(const Mat &binColor3f, Mat &sal1d, float delta, const vector<vector< pair<double, int>>> &similar) { if (sal1d.cols < 2) return; CV_Assert(binColor3f.size() == sal1d.size() && sal1d.rows == 1); int binN = binColor3f.cols; Vec3f* color = (Vec3f*)(binColor3f.data); Mat tmpSal; sal1d.copyTo(tmpSal); float *sal = (float*)(tmpSal.data); float *nSal = (float*)(sal1d.data); //* Distance based smooth int n = max(cvRound(binN / delta), 2); vecF dist(n, 0), val(n); for (int i = 0; i < binN; i++) { const vector< pair<double, int>> &similari = similar[i]; float totalDist = 0; val[0] = sal[i]; for (int j = 1; j < n; j++) { int ithIdx = similari[j].second; dist[j] = similari[j].first; val[j] = sal[ithIdx]; totalDist += dist[j]; } float valCrnt = 0; for (int j = 0; j < n; j++) valCrnt += val[j] * (totalDist - dist[j]); nSal[i] = valCrnt / ((n - 1) * totalDist); } }