- 操作系统：ubuntu22.04
- OpenCV版本：OpenCV4.9
- IDE:Visual Studio Code
- 编程语言：C++11
算法描述
将一个图像添加到累积图像中。
该函数将 src 或其部分元素添加到 dst 中：
dst ( x , y ) ← dst ( x , y ) + src ( x , y ) if mask ( x , y ) ≠ 0 \texttt{dst} (x,y) \leftarrow \texttt{dst} (x,y) + \texttt{src} (x,y) \quad \text{if} \quad \texttt{mask} (x,y) \ne 0 dst(x,y)←dst(x,y)+src(x,y)ifmask(x,y)=0
该函数支持多通道图像。每个通道独立处理。
cv::accumulate 函数可以用于收集由静止相机拍摄的场景背景的统计数据，并用于进一步的前景-背景分割。
函数原型
void cv::accumulate
(InputArray src,InputOutputArray dst,InputArray mask = noArray()
)
参数
-
参数src 输入图像，类型为 CV_8UC(n)，CV_16UC(n)，CV_32FC(n) 或 CV_64FC(n)，其中 n 是一个正整数。
-
参数dst 累积图像，与输入图像具有相同数量的通道，并且深度为 CV_32F 或 CV_64F。
-
参数mask 可选的操作掩码。
代码示例
#include <iostream>
#include <opencv2/opencv.hpp>int main()
{// 加载一个真实的图像cv::Mat sourceImage = cv::imread( "/media/dingxin/data/study/OpenCV/sources/images/sun2.jpg", cv::IMREAD_COLOR );if ( sourceImage.empty() ){std::cout << "Error loading image" << std::endl;return -1;}// 获取源图像的尺寸和通道数cv::Size imageSize = sourceImage.size();int numChannels = sourceImage.channels();// 输出源图像的尺寸和类型std::cout << "Source Image Size: " << imageSize << std::endl;std::cout << "Source Image Type: " << sourceImage.type() << std::endl;std::cout << "Source Image Channels: " << numChannels << std::endl;// 创建一个空的累积图像cv::Mat cumulativeImage = cv::Mat::zeros(imageSize, CV_32FC(numChannels)); // 累积图像类型为 CV_32FC3// 输出累积图像的尺寸和类型std::cout << "Cumulative Image Size: " << cumulativeImage.size() << std::endl;std::cout << "Cumulative Image Type: " << cumulativeImage.type() << std::endl;std::cout << "Cumulative Image Channels: " << cumulativeImage.channels() << std::endl;// 将源图像转换为浮点类型cv::Mat sourceImageFloat;sourceImage.convertTo(sourceImageFloat, CV_32FC(numChannels), 1.0 / 255.0);// 输出转换后的图像尺寸和类型std::cout << "Converted Image Size: " << sourceImageFloat.size() << std::endl;std::cout << "Converted Image Type: " << sourceImageFloat.type() << std::endl;std::cout << "Converted Image Channels: " << sourceImageFloat.channels() << std::endl;// 创建一个掩码图像cv::Mat mask = cv::Mat::ones(imageSize, CV_8U) * 255; // 全部像素为255，即不使用掩码// 输出掩码图像的尺寸和类型std::cout << "Mask Image Size: " << mask.size() << std::endl;std::cout << "Mask Image Type: " << mask.type() << std::endl;// 确保累积图像和源图像的尺寸一致if (cumulativeImage.rows != sourceImageFloat.rows || cumulativeImage.cols != sourceImageFloat.cols) {std::cout << "Error: Cumulative image and source image do not have the same size." << std::endl;return -1;}// 确保累积图像和源图像的通道数一致if (cumulativeImage.channels() != sourceImageFloat.channels()) {std::cout << "Error: Cumulative image and source image do not have the same number of channels." << std::endl;return -1;}// 累积源图像到累积图像中int numAccumulations = 100; // 增加累加次数for (int i = 0; i < numAccumulations; ++i) {cv::accumulate(sourceImageFloat, cumulativeImage, mask);}// 显示累积图像cv::Mat normalizedCumulativeImage;cv::normalize(cumulativeImage, normalizedCumulativeImage, 0, 255, cv::NORM_MINMAX, CV_8U);// 使用高对比度的色彩映射cv::Mat enhancedCumulativeImage;cv::applyColorMap(normalizedCumulativeImage, enhancedCumulativeImage, cv::COLORMAP_JET);cv::imshow("Original Image", sourceImage);cv::imshow("Cumulative Image", enhancedCumulativeImage);cv::waitKey( 0 );return 0;
}
运行结果
