图像的常规边缘检测(梯度算子、Roberts算子和Sobel算子)之c++实现（qt + 不调包）_c

/*梯度法边缘检测 比例scale对差分结果进行缩放*/
QImage* MainWindow:: SideGrandiant(QImage* image,double scale)
{
    QImage* newImage = new QImage(image->width(),image->height(),QImage::Format_ARGB32);
    QColor color0;
    QColor color1;
    QColor color2;
    int  r = 0;
    int g = 0;
    int b = 0;
    int rgb = 0;
    int r1 = 0;
    int g1 = 0;
    int b1 = 0;
    int rgb1 = 0;
    int a = 0;
    for( int y = 0; y < image->height() - 1; y++)
    {
        for(int x = 0; x < image->width() - 1; x++)
        {
            color0 =   QColor ( image->pixel(x,y));
            color1 =   QColor ( image->pixel(x + 1,y));
            color2 =   QColor ( image->pixel(x,y + 1));
            r = abs(color0.red() - color1.red());
            g = abs(color0.green() - color1.green());
            b = abs(color0.blue() - color1.blue());
            rgb = r + g + b;

            r1 = abs(color0.red() - color2.red());
            g1= abs(color0.green() - color2.green());
            b1 = abs(color0.blue() - color2.blue());
            rgb1 = r1 + g1 + b1;

            a = rgb + rgb1;
            a = a * scale;
            a = a>255?255:a;

            newImage->setPixel(x,y,qRgb(a,a,a));
        }
    }
    return newImage;
}

/*Roberts法边缘检测 比例scale对差分结果进行缩放*/
QImage* MainWindow:: SideRobertsdiant(QImage* image,double scale)
{
    QImage* newImage = new QImage(image->width(),image->height(),QImage::Format_ARGB32);
    QColor color0;
    QColor color1;
    QColor color2;
    QColor color3;
    int  r = 0;
    int g = 0;
    int b = 0;
    int rgb = 0;
    int r1 = 0;
    int g1 = 0;
    int b1 = 0;
    int rgb1 = 0;
    int a = 0;
    for( int y = 0; y < image->height() - 1; y++)
    {
        for(int x = 0; x < image->width() - 1; x++)
        {
            color0 =   QColor ( image->pixel(x,y));
            color1 =   QColor ( image->pixel(x + 1,y));
            color2 =   QColor ( image->pixel(x,y + 1));
            color3 =   QColor ( image->pixel(x + 1,y + 1));
            r = abs(color0.red() - color3.red());
            g = abs(color0.green() - color3.green());
            b = abs(color0.blue() - color3.blue());
            rgb = r + g + b;

            r1 = abs(color1.red() - color2.red());
            g1= abs(color1.green() - color2.green());
            b1 = abs(color1.blue() - color2.blue());
            rgb1 = r1 + g1 + b1;

            a = rgb + rgb1;
            a = a * scale;
            a = a>255?255:a;

            newImage->setPixel(x,y,qRgb(a,a,a));
        }
    }
    return newImage;
}

/*sobel法边缘检测 比例scale对差分结果进行缩放,type表示使用那种公式 取值0或则1*/
QImage* MainWindow:: SideSobeldiant(QImage* image,double scale,int type)
{
    QImage* newImage = new QImage(image->width(),image->height(),QImage::Format_ARGB32);
    QColor color0;
    QColor color1;
    QColor color2;
    QColor color3;
    QColor color4;
    QColor color5;
    QColor color6;
    QColor color7;
    QColor color8;
    int  r = 0;
    int g = 0;
    int b = 0;
    int rgb = 0;
    int r1 = 0;
    int g1 = 0;
    int b1 = 0;
    int rgb1 = 0;
    int a = 0;
    for( int y = 1; y < image->height() - 1; y++)
    {
        for(int x = 1; x < image->width() - 1; x++)
        {
            color0 =   QColor ( image->pixel(x,y));

            color1=   QColor ( image->pixel(x-1,y-1));
            color2 =   QColor ( image->pixel(x,y-1));
            color3 =   QColor ( image->pixel(x+1,y));

            color4 =   QColor ( image->pixel(x-1,y));
            color5 =   QColor ( image->pixel(x+1,y));

            color6 =   QColor ( image->pixel(x-1,y+1));
            color7=   QColor ( image->pixel(x,y+1));
            color8 =   QColor ( image->pixel(x+1,y+1));
            r = abs(color1.red() + color2.red() * 2 + color3.red() - color6.red() - color7.red() * 2 - color8.red());
            g = abs(color1.green() + color2.green() * 2 + color3.green() - color6.green() - color7.green() * 2 - color8.green());
            b = abs(color1.blue() + color2.blue() * 2 + color3.blue() - color6.blue() - color7.blue() * 2 - color8.blue());
            rgb = r + g + b;

            r1 = abs(color1.red() + color4.red() * 2 + color6.red() - color3.red() - color5.red() * 2 - color8.red());
            g1= abs(color1.green() + color4.green() * 2 + color6.green() - color3.green() - color5.green() * 2 - color8.green());
            b1 = abs(color1.blue() + color4.blue() * 2 + color6.blue() - color3.blue() - color5.blue() * 2 - color8.blue());
            rgb1 = r1 + g1 + b1;
           if(type == 0)
           {
               if (rgb > rgb1)
                   a = rgb;
               else
                   a = rgb1;
           }
           else if(type == 1)
           {
            a = (rgb + rgb1)/2;
           }
            a = a * scale;
            a = a>255?255:a;

            newImage->setPixel(x,y,qRgb(a,a,a));


**收集整理了一份《2024年最新物联网嵌入式全套学习资料》，初衷也很简单，就是希望能够帮助到想自学提升的朋友。**
![img](https://p6-xtjj-sign.byteimg.com/tos-cn-i-73owjymdk6/a9e235fe12a24a749577650c0d97132d~tplv-73owjymdk6-jj-mark-v1:0:0:0:0:5o6Y6YeR5oqA5pyv56S-5Yy6IEAg5py65Zmo5a2m5Lmg5LmL5b-DQUk=:q75.awebp?rk3s=f64ab15b&x-expires=1771259498&x-signature=QizARqwu0sHGW7i8Irv36NZ42u0%3D)
![img](https://p6-xtjj-sign.byteimg.com/tos-cn-i-73owjymdk6/003c8cd997284fedb83747e4c34731e5~tplv-73owjymdk6-jj-mark-v1:0:0:0:0:5o6Y6YeR5oqA5pyv56S-5Yy6IEAg5py65Zmo5a2m5Lmg5LmL5b-DQUk=:q75.awebp?rk3s=f64ab15b&x-expires=1771259498&x-signature=KAIIExrAEYUdUUjCvZsd1GEyxuA%3D)

**[如果你需要这些资料，可以戳这里获取](https://gitee.com/vip204888)**

**一个人可以走的很快，但一群人才能走的更远！不论你是正从事IT行业的老鸟或是对IT行业感兴趣的新人**

**都欢迎加入我们的的圈子（技术交流、学习资源、职场吐槽、大厂内推、面试辅导），让我们一起学习成长！**