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source/_posts/2026/2026.3/opencv-1.md

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+---
+title: opencv基础操作
+categories:
+  - 技术
+series: opencv
+tags:
+  - opencv
+abbrlink: e8f95ead
+summary: >-
+  这篇文章介绍了使用C++和OpenCV库进行图像处理的基础操作，包括图片的读取与展示、像素的读取与修改、图像的基本变换（缩放、旋转、平移、翻转）、以及图像通道的分离与合并。文章详细讲解了每个操作的代码实现，并展示了如何通过OpenCV库提供的函数来完成这些任务。这对于初学者来说是非常有用的，因为它帮助他们理解如何使用OpenCV进行图像处理。
+date: 2026-03-15 09:56:51
+---
+
+这里用C++进行编程，发现菜鸟教程只有python的版本，那就记录一下。
+
+# 图片读取与展示
+
+```cpp
+// 读取图像
+#include<opencv2/opencv.hpp>
+#include<iostream>
+
+using namespace std;
+using namespace cv;
+
+int main(){
+    Mat src = imread("../img/1.png");
+    imshow("input",src);
+    waitKey(0);
+    destroyAllWindows();
+    return 0;
+}
+```
+
+# 图像基本操作
+## 读取像素
+需要用到三维向量数组Vect3b，这里需要注意的是，Opencv是BGR而不是我们常用的RGB。
+```cpp
+// 读取像素
+#include<opencv2/opencv.hpp>
+#include<iostream>
+
+using namespace std;
+using namespace cv;
+
+int main()
+{
+    string image_path = "../img/1.png";
+    Mat image = imread(image_path);
+
+    if (image.empty()) {
+        cout << "错误：无法加载图像，请检查路径是否正确。" << endl;
+        return -1;
+    }
+
+    Vec3b pixel_value = image.at<Vec3b>(100, 150);
+
+    cout << "B: " << (int)pixel_value[0] << " "
+         << "G: " << (int)pixel_value[1] << " "
+         << "R: " << (int)pixel_value[2] << endl;
+
+}
+```
+
+## 修改像素
+
+```cpp
+// 修改像素
+#include<opencv2/opencv.hpp>
+#include<iostream>
+
+using namespace std;
+using namespace cv;
+
+int main()
+{
+    string image_path = "../img/1.png";
+    Mat image = imread(image_path);
+    Mat result = image.clone();
+
+    if (image.empty()) {
+        cout << "错误：无法加载图像，请检查路径是否正确。" << endl;
+        return -1;
+    }
+
+    Rect roi_rect(0, 0, 100, 100);
+    Mat roi = result(roi_rect);
+    roi.setTo(Scalar(0, 255, 0));
+    imshow("Original (Unchanged)", image);
+    imshow("Modified Copy", result);
+    waitKey(0);
+
+    return 0;
+
+}
+```
+
+```cpp
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+int main() {
+    // 读取图像
+    cv::Mat img = cv::imread("../img/1.png");
+    if (img.empty()) {
+        std::cout << "无法读取图像" << std::endl;
+        return -1;
+    }
+
+    // 1. 缩放
+    cv::Mat resized_img;
+    cv::resize(img, resized_img, cv::Size(200, 200));
+    cv::imshow("resized_img", resized_img);
+
+    // 2. 旋转
+    cv::Mat rotated_img, M_rot;
+    cv::Point2f center(img.cols / 2.0, img.rows / 2.0);
+    M_rot = cv::getRotationMatrix2D(center, 45, 1.0);
+    cv::warpAffine(img, rotated_img, M_rot, img.size());
+    cv::imshow("rotated_img", rotated_img);
+
+    // 3. 平移
+    cv::Mat translated_img;
+    cv::Mat M_trans = (cv::Mat_<float>(2, 3) << 1, 0, 100, 0, 1, 50);
+    cv::warpAffine(img, translated_img, M_trans, img.size());
+    cv::imshow("translated_img", translated_img);
+
+    // 4. 翻转
+    cv::Mat flipped_img;
+    cv::flip(img, flipped_img, 1);
+    cv::imshow("flipped", flipped_img);
+
+    // 显示结果
+    cv::imshow("Original", img);
+    cv::waitKey(0);
+
+    return 0;
+}
+```
+
+```cpp
+// 图像通道分离与合并
+#include<opencv2/opencv.hpp>
+#include<iostream>
+
+using namespace std;
+using namespace cv;
+
+int main()
+{
+    string image_path = "../img/1.png";
+    Mat image = imread(image_path);
+    Mat result = image.clone();
+    // 定义向量数组接收通道
+    vector<Mat> channels;
+    // 拆分
+    split(result,channels);
+
+    Mat b = channels[0];
+    Mat g = channels[1];
+    Mat r = channels[2];
+
+    imshow("Blue Channel (Grayscale)", channels[0]);
+    imshow("Green Channel (Grayscale)", channels[1]);
+    imshow("Red Channel (Grayscale)", channels[2]);
+
+    // merge
+    Mat merged_img;
+    vector<cv::Mat> channels_to_merge;
+    channels_to_merge.push_back(b);
+    channels_to_merge.push_back(g);
+    channels_to_merge.push_back(r);
+
+    merge(channels_to_merge, merged_img);
+    imshow("merged",merged_img);
+
+    waitKey(0);
+
+    return(0);
+}
+```