如何使用OpenCV将偏导数高斯核应用于图像? [英] How to apply a partial derivative Gaussian kernel to an image with OpenCV?

问题描述

我正在尝试从论文中复制结果，在该结果中，它们将图像与高斯核的水平偏导数进行卷积.我还没有找到任何使用OpenCV实现该目标的方法.那可能吗 ?

I'm trying reproduce results from a paper, in which they convolve the image with an horizontal partial derivative of a Gaussian kernel. I haven't found any way to achieve that with OpenCV. Is that possible ?

我是否必须先获得高斯滤波器，然后手动计算偏导数?

Do I have to get Gaussian filter and then compute the partial derivatives by hand ?

推荐答案

OpenCV没有内置函数来计算高斯偏导数.但是您可以使用 cv::getGaussianKernel 和 cv::filter2D 这样做.

OpenCV doesn't have built-in function to calculate Gaussian partial derivatives. But you may use cv::getGaussianKernel and cv::filter2D to do so.

例如:

  cv::Mat kernel = cv::getGaussianKernel(3, 0.85, CV_32F);
  kernel = kernel.reshape(1, 1);
  cv::filter2D(img, img, CV_8U, kernel);

请注意，cv::getGaussianKernel返回列过滤器，因此您需要reshape将其水平放置.

Please note that cv::getGaussianKernel returns column filter, so you need reshape to make it horizontal.

这篇关于如何使用OpenCV将偏导数高斯核应用于图像?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！