[opencv]图像增强与色度增强支持函数

 

 

#include "ImgProcession.h"

/**
 * @brief mat数值累加
 * @param src:矩阵mat
 */

double ImgProcession::matsum(Mat src) {
    //初始化
    double total;
    //翻写numpy的sum函数，可以用来检查图像的数据
    //快速写法
    Scalar ss = sum(src);
    for (int i = 0; i < ss.rows; i++) {
        total = total + ss[i];
    }
    //Eigen写法 需要-O3的编译优化状态下，速度提升10倍
    /*vector mat_split;
    split(src, mat_split);
    Map>
            map_b(mat_split[0].data, mat_split[0].rows, mat_split[0].cols),
            map_g(mat_split[1].data, mat_split[1].rows, mat_split[1].cols),
            map_r(mat_split[2].data, mat_split[2].rows, mat_split[2].cols);
    total = map_b.cast().sum() + map_g.cast().sum() + map_r.cast().sum();*/
    return total;
}

// 注意float类型跟python一样
float value_cast(float value) {
    if (value > 255){
        value = 255;
    } else if (value < 0){
        value = 0;
    }
    return value;
}

/**
 * @brief 亮度增强
 * @param src:图像流
 * @param arr:调整参数,一般取1.15
 * @return dst:新图像
 */
Mat ImgProcession::BrightEnhance(Mat src, double arr) {
    Mat src_T = src.clone();
    int row = src.rows;
    int col = src.cols;
    vector bgr_split, hsv_split;
    split(src_T, bgr_split);
    Mapchar, Dynamic, Dynamic, RowMajor>>
            map_b(bgr_split[0].data, row, col),
            map_g(bgr_split[1].data, row, col),
            map_r(bgr_split[2].data, row, col);

    Mat src_R = src.clone();
    Mat src_hsv;
    cvtColor(src_R, src_hsv, COLOR_BGR2HSV);
    split(src_hsv, hsv_split);
    Mapchar, Dynamic, Dynamic, RowMajor>>
            map_v(hsv_split[2].data, row, col);
    // 计算亮度均值
    double mean_v = map_v.cast<double>().mean();
    double rate_bri = 200 / mean_v;
    // 配置参数
    if (rate_bri > arr) {
        rate_bri = 1.15;
    }
    // 融合图像
    map_b = (map_b.cast<double>() * rate_bri).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_g = (map_g.cast<double>() * rate_bri).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_r = (map_r.cast<double>() * rate_bri).unaryExpr(ptr_fun(value_cast)).castchar>();
    Mat
            mat_dst_b(row, col, CV_8UC1, map_b.data()),
            mat_dst_g(row, col, CV_8UC1, map_g.data()),
            mat_dst_r(row, col, CV_8UC1, map_r.data());
    vector nm;
    nm.emplace_back(move(mat_dst_b));
    nm.emplace_back(move(mat_dst_g));
    nm.emplace_back(move(mat_dst_r));
    Mat dst;
    merge(nm, dst);
    return dst;
}


/**
 * @brief 色度增强
 * @param src:图像流
 * @param arr:调整参数,一般取1.5
 * @return dst:新图像
 */
Mat ImgProcession::ColorEnhance(Mat src, double arr) {
    Mat src_T = src.clone();
    int row = src.rows;
    int col = src.cols;
    vector mat_split;
    split(src_T, mat_split);
    Mapchar, Dynamic, Dynamic, RowMajor>>
            map_b(mat_split[0].data, row, col),
            map_g(mat_split[1].data, row, col),
            map_r(mat_split[2].data, row, col);
    Matrix<int, Dynamic, Dynamic, RowMajor>
            map_f = (map_r.cast<double>() * 0.299 + map_g.cast<double>() * 0.587 + map_b.cast<double>() * 0.114).cast<int>();
    // 融合图像
    map_b = ((map_f.cast<double>() * (1.0 - arr)).array() + (map_b.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_g = ((map_f.cast<double>() * (1.0 - arr)).array() + (map_g.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_r = ((map_f.cast<double>() * (1.0 - arr)).array() + (map_r.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>();
    Mat
            mat_dst_b(row, col, CV_8UC1, map_b.data()),
            mat_dst_g(row, col, CV_8UC1, map_g.data()),
            mat_dst_r(row, col, CV_8UC1, map_r.data());
    vector nm;
    nm.emplace_back(move(mat_dst_b));
    nm.emplace_back(move(mat_dst_g));
    nm.emplace_back(move(mat_dst_r));
    Mat dst;
    merge(nm, dst);
    return dst;
}

/**
 * @brief 对比度增强
 * @param src:图像流
 * @param arr:调整参数,一般取1.5
 * @return dst:新图像
 */
Mat ImgProcession::ContrastEnhance(Mat src, double arr) {
    Mat src_T = src.clone();
    int row = src.rows;
    int col = src.cols;
    vector mat_split;
    split(src_T, mat_split);
    Mapchar, Dynamic, Dynamic, RowMajor>>
            map_b(mat_split[0].data, row, col),
            map_g(mat_split[1].data, row, col),
            map_r(mat_split[2].data, row, col);
    int mean = (map_r.cast<double>() * 0.299 + map_g.cast<double>() * 0.587 + map_b.cast<double>() * 0.114).cast<int>().cast<double>().mean() + 0.5;
    // 融合图像
    map_b = (mean * (1.0 - arr) + (map_b.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_g = (mean * (1.0 - arr) + (map_g.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>(),
    map_r = (mean * (1.0 - arr) + (map_r.cast<double>() * arr).array()).unaryExpr(ptr_fun(value_cast)).castchar>();
    Mat
            mat_dst_b(row, col, CV_8UC1, map_b.data()),
            mat_dst_g(row, col, CV_8UC1, map_g.data()),
            mat_dst_r(row, col, CV_8UC1, map_r.data());
    vector nm;
    nm.emplace_back(move(mat_dst_b));
    nm.emplace_back(move(mat_dst_g));
    nm.emplace_back(move(mat_dst_r));
    Mat dst;
    merge(nm, dst);
    return dst;
}

/**
 * 同时增强对比对颜色
 * @param src
 * @param arr
 * @return
 */
Mat ImgProcession::ContrastAndColorEnhance(Mat src, double con, double co){
    Mat dst = ContrastEnhance(src, con);
    dst = ColorEnhance(dst, co);
    return dst;
}

 

#include 
#include 
#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;
using namespace Eigen;

class ImgProcession {

public:
    static double matsum(Mat src);
    static Mat BrightEnhance(Mat src, double arr=1.15);
    static Mat ColorEnhance(Mat src, double arr=1.5);
    static Mat ContrastEnhance(Mat src, double arr=1.5);
    static Mat ContrastAndColorEnhance(Mat src, double con, double col);
};

 

转载于:https://www.cnblogs.com/lx17746071609/p/11507643.html