本次案例分享是来自美国的一个作业代写，主要是关于数学的一个assignment的Matlab代写

I: Edge Detection using Multiscale LOG Detectors

Find all the edges in an image of your choice using multiscale LOG filters, i.e.,2G . Specifically, you need to implement the following:
(1) Blur the image with Gaussian filters (i.e., G) at several different scales (e.g.,  2,8,16). Show the blurred images to illustrate the multiscale idea.

(2) Apply LOG filters (2G ) with the scales you choose in (1) to detect edges.

a) Show the output images filtered by 2G ; [Note that there are positive and negative values. Hence you shall display zero value in gray (128).]

b) Display the LOG-filtered images with positive values in white (255) and negative in black (0);

c) Display the zero-crossings.

d) (Bonus – 5 points) Combine the multiscale zero-crossings to obtain the final edge map.

II: Edge Detection using Canny Edge Detectors

Find all the edges in an image of your choice using Canny edge detectors.Specifically, you need to implement the following:

(1) Blur the image with Gaussian filters (i.e., G) at several different scales (e.g.,  2,8,16). Show the blurred images to illustrate the multiscale idea.

(2) Apply Canny edge detectors with the scales you choose in (1) to detect edges.

a) Show the magnitude and angle, respectively, of the gradient images after applying Canny edge filters (i.e., the 1st derivative ofGaussians);

b) Display the edges before and after non-maximum suppression.

c) Display the final edge maps after edge linking (or the double-thresholding technique).