[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

  1 //my_hw1.cpp
  2 #include <stdio.h>
  3 #include<iostream>
  4 #include <opencv2/opencv.hpp>
  5 #include<opencv2/core/core.hpp>
  6 #include<opencv2/highgui/highgui.hpp>
  7
  8 using namespace cv;
  9 using namespace std;
 10
 11 string my_pic = "07.png";
 12 Mat image = imread(my_pic, CV_LOAD_IMAGE_GRAYSCALE);
 13
 14 void on_trackbar(int p, void*) {
 15
 16 //************************Scale***************************
 17         //每次回调都重新载入图像
 18     Mat src = imread(my_pic, CV_LOAD_IMAGE_GRAYSCALE);
 19
 20         //获取三个滑动条的值
 21     int c = cvGetTrackbarPos("Width", "after change");
 22     int r = cvGetTrackbarPos("Height", "after change");
 23     int level = cvGetTrackbarPos("Level", "after change");
 24
 25         //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）
 26     int sh = src.rows;
 27     int sw = src.cols;
 28     int sx, sy;
 29
 30         //重置后的新图片
 31     Mat dst(r, c, src.type());
 32
 33         //填充新图片的像素
 34     for (int i = 0; i < r; i ++) {
 35         for (int j = 0; j < c; j ++) {
 36             double x = i / (r + 0.0);
 37             double y = j / (c + 0.0);
 38             sx = sh * x;
 39             sy = sw * y;
 40             dst.at<uchar>(i, j) = src.at<uchar>(sx,sy);
 41         }
 42     }
 43
 44 //********************Quantization************************
 45
 46     //使得level的值合法
 47     if (level <= 256 && level >= 128)level = 128;
 48     else if(level < 128 && level >= 64)level = 64;
 49     else if(level < 64 && level >= 32)level = 32;
 50     else if(level < 32 && level >= 16) level = 16;
 51     else if(level < 16 && level >= 8)level = 8;
 52     else if(level < 8 && level >= 4)level = 4;
 53     else level = 2;
 54
 55     int channels = dst.channels();
 56     int nrows = dst.rows;
 57     int ncols = dst.cols * channels;
 58
 59     uchar table[256];
 60     int degree = 255/(level - 1);
 61     int number = 256 / level;
 62     int count = 0;
 63     int value = 0;
 64
 65         //设定好要求的灰度映射
 66     for (int i = 0; i < 256; i ++, count ++) {
 67         if (count < number) table[i] = value;
 68         else {
 69             count = 0;
 70             value += degree;
 71             table[i] = value;
 72         }
 73     }
 74
 75     if (src.isContinuous()) {
 76         ncols *= nrows;
 77         nrows = 1;
 78     }
 79
 80     for (int i = 0; i < nrows; i ++) {
 81         uchar *p = dst.ptr<uchar>(i);
 82         for (int j = 0; j < ncols; j ++) {
 83             p[j] = table[p[j]];
 84         }
 85     }
 86
 87     //cout << level << " " << c << " " << r << "\n";
 88         imshow("after change", dst);
 89 }
 90
 91 int main( int argc, char** argv) {
 92     imshow("before change", image);
 93
 94     int width = 384;
 95     int height = 256;
 96     int level = 256;
 97     namedWindow("after change", CV_WINDOW_AUTOSIZE);
 98     createTrackbar( "Width", "after change", &width, 800, on_trackbar);
 99     createTrackbar( "Height", "after change", &height, 500, on_trackbar);
100     createTrackbar( "Level", "after change", &level, 256, on_trackbar); //slider
101
102     on_trackbar(0, 0);
103
104     waitKey();
105     return 0;
106 }
107     

另外，我选择的编译方式是cmake + make;

CMakeLists.txt

1 cmake_minimum_required(VERSION 2.8)
2 project( my_hw1 )
3 find_package( OpenCV REQUIRED )
4 add_executable( my_hw1 my_hw1.cpp )
5 target_link_libraries( my_hw1 ${OpenCV_LIBS} )

CMakeLists.txt

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：