专栏地址:http://blog.csdn.net/column/details/imagep.html
本篇文章主要记录一下图像处理软件中的图像特效(素描和油画)的实现过程。
图像素描效果
图像素描的实现原理其实很简单,主要是利用边缘检测滤波器来实现。
可供选择的边缘检测滤波器有很多,常用的有Sobel、Scharr、Laplacian以及Canny滤波。本文主要是利用Laplacian来实现素描化,它的效果相对于Sobel和Scharr更加相像素描效果。
Laplacian算子是一个二阶导数算子,具有各向同性,即与坐标轴方向无关,坐标轴旋转后梯度结果不变。但是,它对噪声比较敏感,所以我们这里先利用中值滤波器对图像进行去噪处理。
Laplacian常用的卷积核来近似,如下图所示:
Code:
void MainWindow::on_actionSketch_triggered() { cv::Mat gray; cv::cvtColor(image,gray,CV_BGR2GRAY); const int MEDIAN_BLUR_FILTER_SIZE = 7; cv::medianBlur(gray,gray,MEDIAN_BLUR_FILTER_SIZE); cv::Mat edges; const int LAPLACIAN_FILTER_SIZE = 5; cv::Laplacian(gray,edges,CV_8U,LAPLACIAN_FILTER_SIZE); cv::Mat mask; const int EDGE_THRESHOLD = 50; cv::threshold(edges,mask,EDGE_THRESHOLD,255,cv::THRESH_BINARY_INV); QImage simg = QImage((const unsigned char*)(mask.data),mask.cols,mask.rows, QImage::Format_Indexed8); //ui->Imagedisplaylabel->setPixmap(QPixmap::fromImage(simg)); //ui->Imagedisplaylabel->setScaledContents(true); //ui->Imagedisplaylabel->resize(ui->Imagedisplaylabel->width(),ui->Imagedisplaylabel->height()); }
图像油画效果
关于图像的油画效果,本文是先利用双边滤波器(见我的博客),将图像的区域推平,然后再将上面的素描效果叠加到经滤波后的图像上,如此即可实现图像的油画效果。
Code:
void MainWindow::on_actionCartoon_triggered() { cv::Mat gray; cv::cvtColor(image,gray,CV_BGR2GRAY); const int MEDIAN_BLUR_FILTER_SIZE = 7; cv::medianBlur(gray,gray,MEDIAN_BLUR_FILTER_SIZE); cv::Mat edges; const int LAPLACIAN_FILTER_SIZE = 5; cv::Laplacian(gray,edges,CV_8U,LAPLACIAN_FILTER_SIZE); cv::Mat mask ; const int EDGE_THRESHOLD = 90; cv::threshold(edges,mask,EDGE_THRESHOLD,255,cv::THRESH_BINARY_INV); cv::Size size = image.size(); cv::Size smallSize; smallSize.width = size.width/2; smallSize.height = size.height/2; cv::Mat smallImg = cv::Mat(smallSize,CV_8UC3); cv::resize(image,smallImg,smallSize,0,0,cv::INTER_LINEAR); cv::Mat tmp = cv::Mat(smallSize,CV_8UC3); int repetitions = 9; for (int i = 0; i < repetitions; i++) { int ksize = 9; double sigmaColor = 9; double sigmaSpace = 7; cv::bilateralFilter(smallImg,tmp,ksize,sigmaColor,sigmaSpace); cv::bilateralFilter(tmp,smallImg,ksize,sigmaColor,sigmaSpace); } cv::Mat bigImg; cv::resize(smallImg,bigImg,image.size(),0,0,cv::INTER_LINEAR); cv::Mat cartoon= cv::Mat(image.size(),CV_8UC3); memset((char*)cartoon.data,0,cartoon.step * cartoon.rows); bigImg.copyTo(cartoon,mask); cv::imwrite("./mask1.jpg",cartoon); ui->textBrowser->clear(); ui->textBrowser->append("<img src= ./mask1.jpg>"); }
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