opencv学习：实现matlab中的stretchlim函数

matlab中的imadjust函数的第一种调用方式为：imadjust(I), I为待处理图像，在参数封装时调用了stretchlim函数。但opencv中没有相应的实现，故参照matlab的源代码实现了stretchlim函数。该函数用了上一篇文章中实现的hist函数，

void stretchlim(const IplImage* img, vector<double> tol, vector<double>& low_high){//接受参数double tol_low , tol_high;switch(tol.size()){case 0://默认值为 0.01, 0.99tol_low = 0.01;tol_high = 0.99;break;case 1:tol_low = tol[0];tol_high = 1-tol[0];break;case 2:tol_low = tol[0];tol_high = tol[1];break;}int nbins = 255;if(img->depth == IPL_DEPTH_16U)nbins = 65535;//若容忍度低值小于高值则观察直方图获取灰度范围if(tol_low<tol_high){//计算直方图vector<long> N = hist(img);//计算累积分布向量vector<double> cdp = cumsumativeDistribution(N);//查找tol_low,tol_high边界灰度值int ilow = lower_bound(cdp.begin(), cdp.end(), tol_low)-cdp.begin();int ihigh = upper_bound(cdp.begin(), cdp.end(), tol_high)-cdp.begin();cout<<tol_low<<endl;cout<<tol_high<<endl;cout<<ilow<<endl;cout<<ihigh<<endl;if(ilow == ihigh)//若边界灰度值相等则设为默认值（当图像为一个平面时）{low_high.push_back(0);low_high.push_back(1);}else//否则设为边界灰度归一化值{low_high.push_back(ilow*1.0/nbins);low_high.push_back(ihigh*1.0/nbins);}}//否则设为默认值0,1else{low_high.push_back(0);low_high.push_back(1);}}vector<double> cumsumativeDistribution(vector<long> vec){vector<double> distr;vector<long> cum;long sum = 0;//计算累积向量和总和for(vector<long>::iterator it = vec.begin(); it != vec.end(); it++){sum += *it;cum.push_back(sum);}//计算累积分布率向量for(vector<long>::iterator it = cum.begin(); it != cum.end(); it++){distr.push_back(*it*1.0/sum);}return distr;}