OpenCV：使用高斯模糊裁剪图像

Question

我有一个灰度图像，我想裁剪一个大小为w x h的矩形，其中心位于像素(x,y)。问题是，我不希望裁剪看起来很宽松，所以我想要高斯模糊值，以便它们平滑地过渡到零。关于如何做到这一点的任何想法？

目前我在做：

int bb_min_x = center_x - width/2.0;
int bb_max_x = center_x + width/2.0;

int bb_min_y = center_y - height/2.0;
int bb_max_y = center_y + height/2.0;

for(int y = bb_min_y; y <= bb_max_y; y++){
    for(int x = bb_min_x; x <= bb_max_x; x++){
        final_img.at<uchar>(y,x) = original_img.at<uchar>(y,x);
    }
}

Answer 1

尝试此功能：

计算输入矩形的距离，并将其用作衰落因子。

cv::Mat cropFade(cv::Mat _img, cv::Rect _roi, int _maxFadeDistance)
{
cv::Mat fadeMask = cv::Mat::ones(_img.size(), CV_8UC1);
cv::rectangle(fadeMask, _roi, cv::Scalar(0),-1);

cv::imshow("mask",fadeMask>0);

cv::Mat dt;
cv::distanceTransform(fadeMask > 0, dt, CV_DIST_L2 ,CV_DIST_MASK_PRECISE);



// fade to a maximum distance:
double maxFadeDist;

if(_maxFadeDistance > 0)
    maxFadeDist = _maxFadeDistance;
else
{
    // find min/max vals
    double min,max;
    cv::minMaxLoc(dt,&min,&max);
    maxFadeDist = max;
}


//dt = 1.0-(dt* 1.0/max);   // values between 0 and 1 since min val should alwaysbe 0
dt = 1.0-(dt* 1.0/maxFadeDist); // values between 0 and 1 in fading region

cv::imshow("blending mask", dt);


cv::Mat imgF;
_img.convertTo(imgF,CV_32FC3);


std::vector<cv::Mat> channels;
cv::split(imgF,channels);
// multiply pixel value with the quality weights for image 1
for(unsigned int i=0; i<channels.size(); ++i)
    channels[i] = channels[i].mul(dt);

cv::Mat outF;
cv::merge(channels,outF);

cv::Mat out;
outF.convertTo(out,CV_8UC3);



return out;
}

用cv::Mat out = cropFade(in, cv::Rect(in.cols/4, in.rows/4, in.cols/2, in.rows/2), in.cols/8);调用它会给我带有指定rect的lena的结果：

这是从同一个未更改的矩形中完整图像淡出的结果：

Answer 2

一种简单的方法：

// Create a weight image
int border=25;
cv::Mat_<float> rect=cv::Mat_<float>::zeros(height,width)
cv::rectangle(rect,cv::Rect(border/2,border/2,width-border,height-border),cv::Scalar(1),-1);
cv::Mat_<float> weights, kernel=cv::getStructuringElement(cv::MORPH_ELLIPSE,cv::Size(border,border));
int nnz = cv::countNonZero(kernel);
cv::filter2D(rect,weights,-1,kernel/nnz);

这将创建如下重量图像：

然后你用它来淡出你的图像：

for(int y = bb_min_y; y <= bb_max_y; y++){
    for(int x = bb_min_x; x <= bb_max_x; x++){
        float w = weights.at<float>(y-bb_min_y,x-bb_min_x);
        uchar val = original_img.at<uchar>(y,x);
        final_img.at<uchar>(y,x) = cv::saturate_cast<uchar>(w*val);
    }
}

Answer 3

如果将边界框转换为轮廓，可以使用pointPolygonTest计算每个像素到边界框边缘的距离。如果您根据此距离将颜色值降低到零，则会产生模糊效果。

有关示例，请参阅this page。