The image processing --- "pixel index image acquisition, processing pixel range, mask applying"

Image processing --- "picture mask processing -> increase the brightness of the image."

　　Learning: For a picture, (1) how to obtain pixel index image, (2) processing pixel range, (3) application of a mask

/ * **************************** ************************************** 
author: @ WP20190612 
environment: VS2010 + OpenCV2.4.3 
function : --- masking operation to improve the contrast of the image 
description: 
    knowledge 1: image acquisition pixel index 
    CV_Assert (myImage.depth () == CV_8U); 
    Mat.ptr <UCHAR> (int I = 0); obtaining the pixel matrix pointers, index i denotes the first few lines, counts from 0 
    const uchar * current = myImage.ptr <uchar > (row); get a pointer to the current row 
    p (row, col) = current [col]; get the current pixel p (row, col) of the pixel values of 
    points which must be clear --- pixel index may be adjusted, and where not to adjust the 

    knowledge 2: 
    pixel range processing saturate_cast <uchar>, ensure that the RGB values in the range between 0 to 255. 
    saturate_cast <uchar> (- 100) return 0; 
    saturate_cast <UCHAR> (288) returns 255; 
    saturate_cast <UCHAR> (100) returned 100;
 
    knowledge 3:
    --- masking operation to improve the contrast of the image 
**************************************** ********************************************** * / 

// ------------------------------- function: to write the function to achieve image mask operation -------- ------------ 
#include <opencv2 / opencv.hpp> 
#include <the iostream> 
#include <math.h> the using namespace CV; int main ( int argc, char ** the argv)   // argumentss parameters; number of command line arguments argc; { 
    Mat the src, DST; 
    the src = imread ( " D: \\ \\ test001.png example_opencv work_VS2010 \\ " );
     IF (! src.data)

 


 
    { 
        the printf ( "Not Load Image ... Could \ n- " );
         return - . 1 ;    // return a successful completion of this function is 0; return -1 This function is not completed 
    } 
    namedWindow ( " INPUT Image " , CV_WINDOW_AUTOSIZE); 
    imshow ( " INPUT Image " , src); 
    
    // ---------------------------- ------------- start processing image --------------------------
     // int cols = src.cols;                      // single channel 
    int cols = (src.cols- . 1 ) * src.channels ();   // width of the image the number of rows --- multichannel image 
    int offsetX src.channels = ();                // number of channels 
    int rows = src.rows; 
    
    DST = Mat :: zeros (src.size (), src.type ());    // initialize a uniform matrix size of the original image matrix is 0, the processing for storing the image
     // start masking function processing 
    for ( int Row = . 1 ; Row <(rows- . 1 ); Row ++ ) 
    { 
        // Get the pixel position pointer 
        const UCHAR * Current = src.ptr <UCHAR> (Row);     // current pixel position pointer 
        const UCHAR * = previous src.ptr <UCHAR> (row- . 1 );   // before a pixel of the current pixel location pointer 
        const UCHAR * Next src.ptr = <UCHAR> (Row + . 1 );   //After the current cursor pixel position a pixel 
        
        UCHAR * Output = dst.ptr <UCHAR> (Row);
         for ( int COL = offsetX; COL <cols; COL ++ )     
        { 
            // Output [COL] = Current. 5 * [COL] - (Current [COL-offsetX] + Current [COL + offsetX] + Previous [COL] Next + [COL]); // glitch effect 
            Output [COL] = saturate_cast <UCHAR> ( . 5 * Current [COL] - (Current [ offsetX-COL] + Current [COL + offsetX] + Previous [COL] Next + [COL])); // burr mention the effect 
        } 
    
    } 
    namedWindow ( " the Image After mask " , CV_WINDOW_AUTOSIZE); 
    imshow ( "After Image mask The " , DST); 

    // save image 
    imwrite ( " D: \\ \\ test001_result.png example_opencv work_VS2010 \\ " , DST); 
    
    // -------------- -------------- end image processing --------------------------------- ------ 
    
    waitKey ( 0 );
     return  0 ; 
}

/***************************************************************************************
作者：@WP20190612

功能：掩膜操作---提高图像的对比度
说明：
    借用OpenCV中的API---filter2D() 掩膜函数进行
***************************************************************************************/

//-------------------------------功能：filter2D() 进行掩膜处理--------------------
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace cv;

int main (int argc, char** argv)  //argumentss 参数；argc命令行参数个数;
{
    Mat src, dst;
    src = imread("D:\\work_VS2010\\example_opencv\\test001.png");
    if (!src.data)
    {
        printf("could not load image ...\n");
        return -1;   //return 0 成功完成本函数；return -1 未能完成本函数
    }
    namedWindow("input image", CV_WINDOW_AUTOSIZE);
    imshow("input image", src);
    
    //----------------------------开始处理图像---------------------------------------
    //使用filter2D() 掩膜函数
    Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);
    filter2D(src, dst, src.depth(), kernel);

    namedWindow("the image after mask", CV_WINDOW_AUTOSIZE );
    imshow("the image after mask",dst);

    //保存图像
    imwrite("D:\\work_VS2010\\example_opencv\\test001_result.png", dst);
    
    //----------------------------结束处理图像---------------------------------------
    
    waitKey(0);
    return 0;
}