高斯差分算子

高斯差分算子（Difference of Gaussian，DoG）

该算法利用高斯差分算子（Difference of Gaussian, DoG）对图像f(x, y)进行边缘检测：首先通过应用两个不同的高斯低通滤波器对图像进行平滑处理，并随后计算两者之间的差异以获取边缘特征

Gaussian low-pass filtering technique is the convolution operation using a Gaussian kernel with a specific width σ₁.

G_{\sigma_{1}}(x, y) = \frac{1}{\sqrt{2 \pi} \sigma_{1}} \exp \left( - \frac{x^{2} + y^{2}}{2 \sigma_{1}^{2}} \right)

得到平滑图像

g_{1}(x, y) = G_{\sigma_{1}}(x, y) * f(x, y)

2. Gaussian low-pass filtering (a convolution involving a Gaussian kernel with a specific size \sigma_{2})

$G_{\sigma_{2}}(x, y) = \frac{1}{\sqrt{2 \pi} \s