更新数字电路和计算机视觉资料

计算机课/计算机视觉/作业/实验一：图像增强应用实践/计算机视觉-2022280486-周睿星-实验报告1-其他/code/CMakeLists.txt

@@ -0,0 +1,17 @@
+cmake_minimum_required(VERSION 3.25)
+project(cv)
+
+set(OpenCV_DIR C:/opencv/opencv/build)
+
+find_package(OpenCV REQUIRED)
+
+include_directories(${OpenCV_INCLUDE_DIRS})
+set(CMAKE_CXX_STANDARD 17)
+
+add_executable(
+        cv
+        main.cpp
+        src/ImageProcess.cpp
+        include/ImageProcess.h
+)
+target_link_libraries(cv ${OpenCV_LIBS})

计算机课/计算机视觉/作业/实验一：图像增强应用实践/计算机视觉-2022280486-周睿星-实验报告1-其他/code/include/ImageProcess.h

@@ -0,0 +1,20 @@
+//
+// Created by pc on 2024/4/8.
+//
+#include <opencv2/opencv.hpp>
+
+#ifndef CV_IMAGEPROCESS_H
+#define CV_IMAGEPROCESS_H
+namespace ImgProcess {
+    // 获取直方图
+    float* getHist(cv::Mat img);
+    // 归一化直方图
+    void normalizeHist(float* hist);
+    // 获取累积分布函数
+    float* getCDF(float* hist);
+    // 直方图均衡化
+    void equalizeHist(cv::Mat img, cv::Mat& equalized_img);
+    // 伽马变换
+    void powerTransform(cv::Mat img, cv::Mat& power_img, float gamma, float c = 1.0);
+}
+#endif //CV_IMAGEPROCESS_H

计算机课/计算机视觉/作业/实验一：图像增强应用实践/计算机视觉-2022280486-周睿星-实验报告1-其他/code/main.cpp

@@ -0,0 +1,22 @@
+/*
+Created by: Pur1fy
+Date: 2024/4/8
+Author: 周睿星
+学号：2022280486
+Description: This is a simple example of using the ImageProcess class to perform power transformation and histogram equalization on an image.
+*/
+#include "include/ImageProcess.h"
+using namespace cv;
+
+int main() {
+    Mat img = imread("../images/car_3.jpg", IMREAD_GRAYSCALE);
+    Mat power_img;
+    Mat equalized_img;
+    ImgProcess::powerTransform(img, power_img, 0.5);
+    ImgProcess::equalizeHist(img, equalized_img);
+    imshow("Power Img", power_img);
+    imshow("Origin Img", img);
+    imshow("Equalized Img", equalized_img);
+    waitKey(0);
+    return 0;
+}

计算机课/计算机视觉/作业/实验一：图像增强应用实践/计算机视觉-2022280486-周睿星-实验报告1-其他/code/src/ImageProcess.cpp

@@ -0,0 +1,64 @@
+//
+// Created by pc on 2024/4/8.
+//
+#include "../include/ImageProcess.h"
+
+namespace ImgProcess {
+    // 获取直方图
+    float* getHist(cv::Mat img) {
+        // 像素值范围0-255
+        int histSize = 256;
+        float* hist = (float*)malloc(sizeof(float) * histSize);
+        memset(hist, 0, sizeof(float) * histSize);
+        // 遍历图像，统计每个像素值的个数
+        for (int i = 0; i < img.rows; i++) {
+            for (int j = 0; j < img.cols; j++) {
+                hist[img.at<uchar>(i, j)]++;
+            }
+        }
+        return hist;
+    }
+    void normalizeHist(float* hist) {
+        float sum = 0;
+        for (int i = 0; i < 256; i++) {
+            sum += hist[i];
+        }
+        for (int i = 0; i < 256; i++) {
+            hist[i] /= sum;
+        }
+    }
+    // 获取累积分布函数
+    float* getCDF(float* hist) {
+        float* cdf = (float*)malloc(sizeof(float) * 256);
+        cdf[0] = hist[0];
+        for (int i = 1; i < 256; i++) {
+            // 累积分布函数求法：前一个像素的累积分布函数值+当前像素的概率
+            cdf[i] = cdf[i - 1] + hist[i];
+        }
+        return cdf;
+    }
+    void equalizeHist(cv::Mat img, cv::Mat& equalized_img) {
+        float* hist = getHist(img);
+        normalizeHist(hist);
+        float* cdf = getCDF(hist);
+        equalized_img = img.clone();
+        for (int i = 0; i < img.rows; i++) {
+            for (int j = 0; j < img.cols; j++) {
+                // 像素值映射 原像素 --> cdf[原像素] * 255
+                equalized_img.at<uchar>(i, j) = cdf[img.at<uchar>(i, j)] * 255;
+            }
+        }
+        free(hist);
+        free(cdf);
+    }
+    void powerTransform(cv::Mat img, cv::Mat& power_img, float gamma, float c) {
+        power_img = img.clone();
+        float L = 255;
+        for (int i = 0; i < img.rows; i++) {
+            for (int j = 0; j < img.cols; j++) {
+                // 像素值映射 原像素 --> c * (原像素 / L ) ^ gamma * L
+                power_img.at<uchar>(i, j) = c * pow(img.at<uchar>(i, j) / L, gamma) * L;
+            }
+        }
+    }
+}