"高斯梯度滤波与Canny边缘检测"

The Canny Edge Detection algorithm is a widely used method for detecting edges in images. It involves several steps to accurately identify edges in an image. Firstly, the algorithm applies a Gaussian filter to the image to smooth out any noise and create a gradient in the image. This helps in reducing the impact of noise on the edge detection process. Secondly, the algorithm calculates the gradient magnitude for each pixel in the image. This is done by applying the Sobel operator or other gradient operators to determine the strength of the edges at each pixel. Next, the algorithm calculates the edge direction for each pixel based on the gradient values. This information is crucial for determining the orientation of the edges in the image. After that, the algorithm identifies local maxima in the gradient magnitude to determine potential edge points. These local maxima represent the strong edges in the image. Finally, the algorithm connects the edge points to generate continuous edges in the image. This step involves linking adjacent edge points to form coherent edge contours. Overall, the Canny Edge Detection algorithm is a multi-step process that involves filtering, gradient calculation, edge strength determination, edge direction estimation, local maxima detection, and edge linking. By performing these steps, the algorithm is able to accurately identify edges in images and generate a binary edge map that highlights the edges in the image.