场景需求
之前有提到给灰度图上色的需求,在此基础上,还有一种需求,就是基于另一张参考灰度图的色板来给当前的灰度图上色,比如参考灰度图的数值区间为-10到10,颜色从蓝到绿再到红,而当前的灰度图的数据区间为-1到1,若基于参考灰度图的色板确定数据对应的颜色,则当前灰度图的颜色应该在绿色左右波动。
下方为具体实现函数和测试代码。
功能函数代码
- /**
- * @brief GrayToColorFromOther 灰度图上色,基于参考灰度图的色板
- * @param phase1 输入的灰色图像,通道为1,提供色板
- * @param phase2 输入的灰色图像,通道为1,基于phase1的色板绘色
- * @return 上色后的图像
- */
- cv::Mat GrayToColorFromOther(cv::Mat &phase1, cv::Mat &phase2)
- {
- CV_Assert(phase1.channels() == 1);
- CV_Assert(phase2.channels() == 1);
- if (phase1.empty() || phase2.empty())
- {
- cv::Mat result = cv::Mat::zeros(100, 100, CV_8UC3);
- return result;
- }
- cv::Mat temp, result, mask;
- double max1, min1;
- int row = phase2.rows;
- int col = phase2.cols;
- // 确定参考灰度图的数据范围
- cv::minMaxIdx(phase1, &min1, &max1, nullptr, nullptr, phase1 == phase1);
- // 将当前灰度图以参考灰度图的数据范围作标准,进行数据变换
- temp = phase2.clone();
- for (int i = 0; i < row; ++i)
- {
- float *t2 = temp.ptr<float>(i);
- for (int j = 0; j < col; ++j)
- {
- t2[j] = 255.0f*(phase2.at<float>(i, j) - min1) / (max1 - min1);
- }
- }
- 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(phase2.size(), CV_8UC1);
- mask.setTo(255, phase2 == phase2);
-
- // 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());
-
- // 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)
- for (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);
- cv::Mat GrayToColorFromOther(cv::Mat &phase1, cv::Mat &phase2);
-
- int main(void)
- {
- cv::Mat mag, ang,result,result2;
- UnitPolar(2001, mag, ang);
- mag.at<float>(10, 10) = nan("");
- cv::Mat mag2 = mag / 2;
-
- result = GrayToColor(mag);
- result2= GrayToColorFromOther(mag,mag2);
-
- 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
- */
- 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0-255
- cv::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RGB
- for (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;
- }
-
- /**
- * @brief GrayToColorFromOther 灰度图上色,基于参考灰度图的色板
- * @param phase1 输入的灰色图像,通道为1,提供色板
- * @param phase2 输入的灰色图像,通道为1,基于phase1的色板绘色
- * @return 上色后的图像
- */
- cv::Mat GrayToColorFromOther(cv::Mat &phase1, cv::Mat &phase2)
- {
- CV_Assert(phase1.channels() == 1);
- CV_Assert(phase2.channels() == 1);
- if (phase1.empty() || phase2.empty())
- {
- cv::Mat result = cv::Mat::zeros(100, 100, CV_8UC3);
- return result;
- }
- cv::Mat temp, result, mask;
- double max1, min1;
- int row = phase2.rows;
- int col = phase2.cols;
- // 确定参考灰度图的数据范围
- cv::minMaxIdx(phase1, &min1, &max1, nullptr, nullptr, phase1 == phase1);
- // 将当前灰度图以参考灰度图的数据范围作标准,进行数据变换
- temp = phase2.clone();
- for (int i = 0; i < row; ++i)
- {
- float *t2 = temp.ptr<float>(i);
- for (int j = 0; j < col; ++j)
- {
- t2[j] = 255.0f*(phase2.at<float>(i, j) - min1) / (max1 - min1);
- }
- }
- 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(phase2.size(), CV_8UC1);
- mask.setTo(255, phase2 == phase2);
-
- // 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());
-
- // 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)
- for (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;
- }
测试效果
图1 参考灰度图上色效果
图2 基于参考灰度图色板的上色效果
如上图所示,为了方便,我生成了一个2001*2001的图像矩阵,并设置了另一个对比图像,该图像为原图像的1/2,那么原图像就是参考灰度图,而对比图像就是需要基于参考灰度图色板上色的灰度图。图1为参考灰度图的上色效果,图2是基于参考灰度图色板给对比图像上色的效果图。原图像的数据从0-1.3左右,其颜色变化从蓝到绿再到红,而对比图像的数据从0-1.3/2左右,则颜色变化为蓝到绿,满足了前面提到的需求。
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