opencv中resize函数的源码

下面是OpenCV中`resize`函数的源码：

void cv::resize(InputArray src, OutputArray dst, Size dsize, double fx, double fy, int interpolation)
{
    CV_INSTRUMENT_REGION();

    CV_Assert( (src.depth() == CV_8U || src.depth() == CV_32F) && src.channels() <= 4 );

    if( interpolation == INTER_AREA && fx > 1 && fy > 1 )
    {
        fx = 1./fx;
        fy = 1./fy;
        std::swap(dsize.width, dsize.height);
        interpolation = INTER_AREA_RESCALE;
    }

    if( interpolation == INTER_CUBIC || interpolation == INTER_LANCZOS4 )
    {
        fx = saturate_cast<double>(dsize.width)/src.cols;
        fy = saturate_cast<double>(dsize.height)/src.rows;
    }

    if( fx == 0 || fy == 0 )
    {
        dst.release();
        return;
    }

    CV_Assert( (dsize.width > 0 || dsize.height > 0) && (fx > 0 || fy > 0) );

    Mat srcMat = src.getMat();

    if( srcMat.data == dst.getMat().data )
    {
        Mat temp;
        resize(srcMat, temp, dsize, fx, fy, interpolation);
        dst.assign(temp);
        return;
    }

    dst.create(_resize(srcMat, dsize, fx, fy, interpolation));
}

这个函数的实现比较简单，主要是对输入参数进行检查，然后调用了`_resize`函数完成实际的图像缩放操作。在调用`_resize`函数之前，还对一些特殊情况进行了处理，比如当插值方法为`INTER_AREA`时，会先对图像进行缩小再进行放大，以提高放大效果。当插值方法为`INTER_CUBIC`或`INTER_LANCZOS4`时，会根据目标大小和原始图像大小计算出缩放比例`fx`和`fy`。

下面是`_resize`函数的源码：

static Mat _resize(InputArray _src, Size dsize, double fx, double fy, int interpolation)
{
    CV_INSTRUMENT_REGION()

    int depth = _src.depth(), cn = _src.channels();
    if( _src.isContinuous() && !(dsize.width == 0 && dsize.height == 0) )
    {
        dsize.width = dsize.width > 0 ? dsize.width : cvRound(_src.cols*fx);
        dsize.height = dsize.height > 0 ? dsize.height : cvRound(_src.rows*fy);

        if( (dsize.width == _src.cols && dsize.height == _src.rows) ||
            (dsize.width == 0 && dsize.height == 0) )
        {
            return _src.getMat().clone();
        }

        if( cn == 1 || cn == 3 || cn == 4 )
        {
            Mat src = _src.getMat();
            Mat dst(dsize, CV_MAKETYPE(depth, cn));
            if( interpolation == INTER_NEAREST )
            {
                resize_nn<uchar, Vec3b, ResizeNoVec>(src, dst, fx, fy);
            }
            else if( interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_LANCZOS4 )
            {
                if( interpolation == INTER_LINEAR )
                    resize_<uchar, Vec3b, INTER_LINEAR>(src, dst, fx, fy);
                else if( interpolation == INTER_CUBIC )
                    resize_<uchar, Vec3b, INTER_CUBIC>(src, dst, fx, fy);
                else if( interpolation == INTER_LANCZOS4 )
                    resize_<uchar, Vec3b, INTER_LANCZOS4>(src, dst, fx, fy);
            }
            else if( interpolation == INTER_AREA || interpolation == INTER_AREA_RESCALE )
            {
                if( interpolation == INTER_AREA )
                    resize_area<uchar, Vec3b, ResizeNoVec>(src, dst, fx, fy);
                else
                    resize_area<uchar, Vec3b, ResizeNoVec, AreaFast>(src, dst, fx, fy);
            }
            else if( interpolation == INTER_CUBIC2P_LINEAR )
                resize_<uchar, Vec3b, INTER_CUBIC2P_LINEAR>(src, dst, fx, fy);
            else if( interpolation == INTER_CUBIC2P )
                resize_<uchar, Vec3b, INTER_CUBIC2P>(src, dst, fx, fy);
            else if( interpolation == INTER_NEAREST_NEIGHBOUR_EX )
                resize_nn<uchar, Vec3b, ResizeExpanse>(src, dst, fx, fy);
            else if( interpolation == INTER_LINEAR_EX )
                resize_<uchar, Vec3b, INTER_LINEAR_EX>(src, dst, fx, fy);
            else if( interpolation == INTER_CUBIC_EX )
                resize_<uchar, Vec3b, INTER_CUBIC_EX>(src, dst, fx, fy);
            else if( interpolation == INTER_LANCZOS4_EX )
                resize_<uchar, Vec3b, INTER_LANCZOS4_EX>(src, dst, fx, fy);
            else
                CV_Error(Error::StsUnsupportedFormat, "");

            return dst;
        }
    }

    Mat src = _src.getMat();
    return resizeGeneric(src, dsize, fx, fy, interpolation);
}

这个函数根据输入参数的不同，选择不同的缩放方法进行图像缩放。具体而言，它包含了多个重载函数`resize_`和`resize_area`，分别对应了不同的插值方法。其中`resize_`函数是实现了线性、双三次和Lanczos插值方法的通用缩放函数；`resize_nn`函数是实现了最近邻插值方法的通用缩放函数；`resize_area`函数是实现了像素面积关系插值方法的通用缩放函数。这些函数的具体实现可以参考OpenCV源码。