【OpenCV】像素操作的数字图像处理

之前几天捣鼓matlab，用来处理数字图像，矩阵操作什么的，如果忘记线性代数就真的GG了。

在用了matlab被深深地吐槽之后，决定改用opencv，C++貌似也是处理数字图像的很好的工具

1. 在ubuntu上安装opencv

教程可以百度之，都很详细的

2. 像素处理图像：

     （1）根据输入的数据，用邻近取样插值法，缩放图像

              邻近取样插值法原理：http://blog.chinaunix.net/uid-27675161-id-3452025.html

　  （2）根据输入，改变数字图像的灰度分辨率

      （3）此次实验操作用灰度图来实现

3. 直接贴代码+注释吧

//my_hw1.cpp
#include <stdio.h>
#include<iostream>
#include <opencv2/opencv.hpp>
#include<opencv2/core/core.hpp>  
#include<opencv2/highgui/highgui.hpp>

using namespace cv;
using namespace std;

string my_pic = "07.png";
Mat image = imread(my_pic, CV_LOAD_IMAGE_GRAYSCALE);

void on_trackbar(int p, void*) {

//************************Scale***************************
        //每次回调都重新载入图像
    Mat src = imread(my_pic, CV_LOAD_IMAGE_GRAYSCALE);

        //获取三个滑动条的值
    int c = cvGetTrackbarPos("Width", "after change");
    int r = cvGetTrackbarPos("Height", "after change");
    int level = cvGetTrackbarPos("Level", "after change");
        
        //记录原始图的宽高，以及对应的点sx,sy（邻近取样插值法中用到）
    int sh = src.rows;
    int sw = src.cols;
    int sx, sy;

        //重置后的新图片
    Mat dst(r, c, src.type());

        //填充新图片的像素
    for (int i = 0; i < r; i ++) {
        for (int j = 0; j < c; j ++) {
            double x = i / (r + 0.0);
            double y = j / (c + 0.0);
            sx = sh * x;
            sy = sw * y;
            dst.at<uchar>(i, j) = src.at<uchar>(sx,sy);
        }
    }

//********************Quantization************************

    //使得level的值合法
    if (level <= 256 && level >= 128)level = 128;
    else if(level < 128 && level >= 64)level = 64;
    else if(level < 64 && level >= 32)level = 32;
    else if(level < 32 && level >= 16) level = 16;
    else if(level < 16 && level >= 8)level = 8;
    else if(level < 8 && level >= 4)level = 4;
    else level = 2;

    int channels = dst.channels();
    int nrows = dst.rows;
    int ncols = dst.cols * channels;

    uchar table[256];
    int degree = 255/(level - 1);
    int number = 256 / level;
    int count = 0;
    int value = 0;

        //设定好要求的灰度映射
    for (int i = 0; i < 256; i ++, count ++) {
        if (count < number) table[i] = value;
        else {
            count = 0;
            value += degree;
            table[i] = value;
        }
    }

    if (src.isContinuous()) {
        ncols *= nrows;
        nrows = 1;
    }

    for (int i = 0; i < nrows; i ++) {
        uchar *p = dst.ptr<uchar>(i);
        for (int j = 0; j < ncols; j ++) {
            p[j] = table[p[j]];
        }
    }

    //cout << level << " " << c << " " << r << "
";
        imshow("after change", dst);
}

int main( int argc, char** argv) {
    imshow("before change", image);

    int width = 384;
    int height = 256;
    int level = 256;
    namedWindow("after change", CV_WINDOW_AUTOSIZE);
    createTrackbar( "Width", "after change", &width, 800, on_trackbar);
    createTrackbar( "Height", "after change", &height, 500, on_trackbar);
    createTrackbar( "Level", "after change", &level, 256, on_trackbar); //slider

    on_trackbar(0, 0);

    waitKey();
    return 0;
}
    

另外，我选择的编译方式是cmake + make;

CMakeLists.txt

cmake_minimum_required(VERSION 2.8)
project( my_hw1 )
find_package( OpenCV REQUIRED )
add_executable( my_hw1 my_hw1.cpp )
target_link_libraries( my_hw1 ${OpenCV_LIBS} )

把相应的图片放到同目录的文件夹内，进入到该文件夹，输入命令行

cmake .

make

./my_hw1

就可以执行了～～

最后贴上一个运行结果图：