Open CV缩放图像

缩放图像是图像处理中需要经常使用的操作。太小的图像在图像识别中不能很好的处理,需要将其放大,太大的图像不方便储存,需要将其缩小,下面记录OpenCV图片缩放方法。

缩放函数

void resize(InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR )
参数说明:
src – 原图像
dst – 输出图像
dsize – 输出图像大小,如果为0 则通过此公式计算得到:Size(round(fx*src.cols), round(fy*src.rows)),dsize和fx,fy不能全为空
fx – x方向缩放比例
fy – y方向缩放比例
interpolation – 插值方法:
– INTER_NEAREST - a nearest-neighbor interpolation
– INTER_LINEAR - a bilinear interpolation (used by default)
– INTER_AREA - resampling using pixel area relation. It may be a preferred method for
image decimation, as it gives moire’-free results. But when the image is zoomed, it is
similar to the INTER_NEAREST method.
– INTER_CUBIC - a bicubic interpolation over 4x4 pixel neighborhood
– INTER_LANCZOS4 - a Lanczos interpolation over 8x8 pixel neighborhood

使用示例(放大图像)

下面代码演示使用不同的缩放方法放大同一张图片的结果。

int main( int argc, char** argv )
{
    Mat matSrc = imread("oripic.jpg",1);
    Mat matDst_INTER_NEAREST,matDst_INTER_LINEAR,matDst_INTER_AREA,matDst_INTER_CUBIC,matDst_INTER_LANCZOS4;
    //原图使用不同的方法放大5倍后的结果
    resize(matSrc,matDst_INTER_NEAREST,Size(0,0),5,5,INTER_NEAREST);
    resize(matSrc,matDst_INTER_LINEAR,Size(0,0),5,5,INTER_LINEAR);
    resize(matSrc,matDst_INTER_AREA,Size(0,0),5,5,INTER_AREA);
    resize(matSrc,matDst_INTER_CUBIC,Size(0,0),5,5,INTER_CUBIC);
    resize(matSrc,matDst_INTER_LANCZOS4,Size(0,0),5,5,INTER_LANCZOS4);
    namedWindow("OriPicture");
    imshow("OriPicture",matSrc);
    namedWindow("INTER_NEAREST");
    imshow("INTER_NEAREST",matDst_INTER_NEAREST);
    namedWindow("INTER_LINEAR");
    imshow("INTER_LINEAR",matDst_INTER_LINEAR);
    namedWindow("INTER_AREA");
    imshow("INTER_AREA",matDst_INTER_AREA);
    namedWindow("INTER_CUBIC");
    imshow("INTER_CUBIC",matDst_INTER_CUBIC);
    namedWindow("INTER_LANCZOS4");
    imshow("INTER_LANCZOS4",matDst_INTER_LANCZOS4);
    waitKey(0);
}

放大结果:

image

使用示例(缩小图像)

下面代码将指定图片缩小为当前的0.3

int main( int argc, char** argv )
{
    Mat matSrc = imread("oripic1.png",1);
    Mat matDst_INTER_NEAREST,matDst_INTER_LINEAR,matDst_INTER_AREA,matDst_INTER_CUBIC,matDst_INTER_LANCZOS4;
    //原图使用不同的方法放大5倍后的结果
    resize(matSrc,matDst_INTER_NEAREST,Size(0,0),0.3,0.3,INTER_NEAREST);
    resize(matSrc,matDst_INTER_LINEAR,Size(0,0),0.3,0.3,INTER_LINEAR);
    resize(matSrc,matDst_INTER_AREA,Size(0,0),0.3,0.3,INTER_AREA);
    resize(matSrc,matDst_INTER_CUBIC,Size(0,0),0.3,0.3,INTER_CUBIC);
    resize(matSrc,matDst_INTER_LANCZOS4,Size(0,0),0.3,0.3,INTER_LANCZOS4);
    namedWindow("OriPicture",WINDOW_AUTOSIZE);
    imshow("OriPicture",matSrc);
    namedWindow("INTER_NEAREST",WINDOW_AUTOSIZE);
    imshow("INTER_NEAREST",matDst_INTER_NEAREST);
    namedWindow("INTER_LINEAR");
    imshow("INTER_LINEAR",matDst_INTER_LINEAR);
    namedWindow("INTER_AREA");
    imshow("INTER_AREA",matDst_INTER_AREA);
    namedWindow("INTER_CUBIC");
    imshow("INTER_CUBIC",matDst_INTER_CUBIC);
    namedWindow("INTER_LANCZOS4");
    imshow("INTER_LANCZOS4",matDst_INTER_LANCZOS4);
    waitKey(0);
}

缩小效果(方法名没有在图像中显示,可以自行运行代码查看效果)

image

原文地址:https://www.cnblogs.com/Reyzal/p/5550009.html