Function: Approximate operation of Laplacian of Gaussian;
The Laplacian of Gaussian operator is also called LOG (Laplacian of Gaussian) operator, which is an operator obtained by using the Laplacian to extract edges on the basis of the Gaussian function.
The Laplacian is a high-pass filter , which is the sum of the second-order partial derivatives of the image gray function in two vertical directions. In the case of discrete digital images, the second-order difference of the gray level of the image is directly used to replace the second-order partial derivative in the continuous case, which is very sensitive to noise, and false edge responses often appear when extracting edges. In order to overcome the shortcomings of the Laplacian operator, it is advisable to perform low-pass filtering on the digital image first to suppress noise. The Gaussian function is a good normalized low-pass filter , which can be used for low-pass filtering of digital images to reduce the influence of noise. On this basis, the Laplacian operator is used to extract the edges, which is Gaussian- Laplacian operator, also known as LOG (Laplacian of Gaussian) operator.
Parameter translation (the order corresponds to the order of the above parameters):
Input image,
Output image,
Smoothing coefficient (0.2 ≤ Sigma ≤ 50.0),
Ratio of standard deviation (0.1 ≤ SigFactor ≤ 10.0)
description:
diff_of_gauss uses the difference of Gaussian to approximate the Laplacian Gaussian operator. The standard deviation of these Gaussian functions can be calculated. There are input parameters Sigma and input parameters SigFactor, and the following formula can be used to calculate the output image:
