场景需求

最近有客户提出，想要将解包裹图像转化为有颜色的图像，具备更佳的视觉效果。解包裹图是一个float类型的灰度图像，里面的数值范围类似于从-10.25到20.56这种，客户想要最低的数值为蓝色，最高的数值为红色，中间的数值为绿色。

针对该需求，我们首先需要将灰度值图转化为0-255的8通道(uchar)灰度图，运用归一化函数可以实现，之后考虑到颜色和灰度的关系，比如最低的颜色为蓝色（0,0,255）对应灰度值0，最高的颜色为红色（255,0,0）对应灰度值255，只需要找出其变化的规律即可。

下方为具体实现函数和测试代码。

功能函数代码

/*** @brief GrayToColor                      灰度图上色* @param phase                            输入的灰色图像，通道为1* @return                                 上色后的图像*/
static cv::Mat GrayToColor(cv::Mat &phase)
{CV_Assert(phase.channels() == 1);cv::Mat temp, result, mask;// 将灰度图重新归一化至0-255cv::normalize(phase, temp, 255, 0, cv::NORM_MINMAX);temp.convertTo(temp, CV_8UC1);// 创建掩膜，目的是为了隔离nan值的干扰mask = cv::Mat::zeros(phase.size(), CV_8UC1);mask.setTo(255, phase == phase);// 初始化三通道颜色图cv::Mat color1, color2, color3;color1 = cv::Mat::zeros(temp.size(), temp.type());color2 = cv::Mat::zeros(temp.size(), temp.type());color3 = cv::Mat::zeros(temp.size(), temp.type());int row = phase.rows;int col = phase.cols;// 基于灰度图的灰度层级，给其上色，最底的灰度值0为蓝色（255，0,0），最高的灰度值255为红色（0,0,255），中间的灰度值127为绿色（0,255,0）// 不要惊讶蓝色为什么是（255,0,0），因为OpenCV中是BGR而不是RGBfor (int i = 0; i < row; ++i){uchar *c1 = color1.ptr<uchar>(i);uchar *c2 = color2.ptr<uchar>(i);uchar *c3 = color3.ptr<uchar>(i);uchar *r = temp.ptr<uchar>(i);uchar *m = mask.ptr<uchar>(i);for (int j = 0; j < col; ++j){if (m[j] == 255){if (r[j] > (3 * 255 / 4) && r[j] <= 255){c1[j] = 255;c2[j] = 4 * (255 - r[j]);c3[j] = 0;}else if (r[j] <= (3 * 255 / 4) && r[j] > (255 / 2)){c1[j] = 255 - 4 * (3 * 255 / 4 - r[j]);c2[j] = 255;c3[j] = 0;}else if (r[j] <= (255 / 2) && r[j] > (255 / 4)){c1[j] = 0;c2[j] = 255;c3[j] = 4 * (255 / 2 - r[j]);}else if (r[j] <= (255 / 4) && r[j] >= 0){c1[j] = 0;c2[j] = 255 - 4 * (255 / 4 - r[j]);c3[j] = 255;}else {c1[j] = 0;c2[j] = 0;c3[j] = 0;}}}}// 三通道合并，得到颜色图vector<cv::Mat> images;images.push_back(color3);images.push_back(color2);images.push_back(color1);cv::merge(images, result);return result;
}

C++测试代码

#include<iostream>
#include<opencv2/opencv.hpp>
#include<ctime>
using namespace std;
using namespace cv;
void UnitPolar(int squaresize, cv::Mat& mag,cv::Mat& ang);
void UnitCart(int squaresize, cv::Mat& x, cv::Mat& y);
cv::Mat GrayToColor(cv::Mat &phase);
int main(void)
{cv::Mat mag, ang,result,result3;UnitPolar(2001, mag, ang);mag.at<float>(10, 10) = nan("");clock_t start, end;start = clock();result= GrayToColor(mag);end = clock();double diff = end - start;cout << "time:" << diff/ CLOCKS_PER_SEC << endl;system("pause");return 0;
}
void UnitPolar(int squaresize, cv::Mat& mag,cv::Mat& ang) {cv::Mat x;cv::Mat y;UnitCart(squaresize, x, y);                //产生指定范围内的指定数量点数，相邻数据跨度相同// OpenCV自带的转换有精度限制，导致结果有一定差异性//cv::cartToPolar(x, y, mag, ang, false); //坐标转换mag = cv::Mat(x.size(), x.type());ang = cv::Mat(x.size(), x.type());int row = mag.rows;int col = mag.cols;float *m, *a, *xx, *yy;for (int i = 0; i < row; ++i){m = mag.ptr<float>(i);a = ang.ptr<float>(i);xx = x.ptr<float>(i);yy = y.ptr<float>(i);for (int j = 0; j < col; ++j){m[j] = sqrt(xx[j] * xx[j] + yy[j] * yy[j]);a[j] = atan2(yy[j], xx[j]);}}
}void UnitCart(int squaresize, cv::Mat& x, cv::Mat& y) {CV_Assert(squaresize % 2 == 1);x.create(squaresize, squaresize, CV_32FC1);y.create(squaresize, squaresize, CV_32FC1);//设置边界x.col(0).setTo(-1.0);x.col(squaresize - 1).setTo(1.0f);y.row(0).setTo(1.0);y.row(squaresize - 1).setTo(-1.0f);float delta = 2.0f / (squaresize - 1.0f);  //两个元素的间隔//计算其他位置的值for (int i = 1; i < squaresize - 1; ++i) {x.col(i) = -1.0f + i * delta;y.row(i) = 1.0f - i * delta;}
}/*** @brief GrayToColor                      灰度图上色* @param phase                            输入的灰色图像，通道为1* @return                                 上色后的图像*/
static cv::Mat GrayToColor(cv::Mat &phase)
{CV_Assert(phase.channels() == 1);cv::Mat temp, result, mask;// 将灰度图重新归一化至0-255cv::normalize(phase, temp, 255, 0, cv::NORM_MINMAX);temp.convertTo(temp, CV_8UC1);// 创建掩膜，目的是为了隔离nan值的干扰mask = cv::Mat::zeros(phase.size(), CV_8UC1);mask.setTo(255, phase == phase);// 初始化三通道颜色图cv::Mat color1, color2, color3;color1 = cv::Mat::zeros(temp.size(), temp.type());color2 = cv::Mat::zeros(temp.size(), temp.type());color3 = cv::Mat::zeros(temp.size(), temp.type());int row = phase.rows;int col = phase.cols;// 基于灰度图的灰度层级，给其上色，最底的灰度值0为蓝色（255，0,0），最高的灰度值255为红色（0,0,255），中间的灰度值127为绿色（0,255,0）// 不要惊讶蓝色为什么是（255,0,0），因为OpenCV中是BGR而不是RGBfor (int i = 0; i < row; ++i){uchar *c1 = color1.ptr<uchar>(i);uchar *c2 = color2.ptr<uchar>(i);uchar *c3 = color3.ptr<uchar>(i);uchar *r = temp.ptr<uchar>(i);uchar *m = mask.ptr<uchar>(i);for (int j = 0; j < col; ++j){if (m[j] == 255){if (r[j] > (3 * 255 / 4) && r[j] <= 255){c1[j] = 255;c2[j] = 4 * (255 - r[j]);c3[j] = 0;}else if (r[j] <= (3 * 255 / 4) && r[j] > (255 / 2)){c1[j] = 255 - 4 * (3 * 255 / 4 - r[j]);c2[j] = 255;c3[j] = 0;}else if (r[j] <= (255 / 2) && r[j] > (255 / 4)){c1[j] = 0;c2[j] = 255;c3[j] = 4 * (255 / 2 - r[j]);}else if (r[j] <= (255 / 4) && r[j] >= 0){c1[j] = 0;c2[j] = 255 - 4 * (255 / 4 - r[j]);c3[j] = 255;}else {c1[j] = 0;c2[j] = 0;c3[j] = 0;}}}}// 三通道合并，得到颜色图vector<cv::Mat> images;images.push_back(color3);images.push_back(color2);images.push_back(color1);cv::merge(images, result);return result;
}