Apply Sobel, Prewitt, Laplacian of Gaussian, and Canny edge detector on lena image provided with

this document. Quantitively analyze the performance $($using RMSE metric$)$ of above$-$mentioned

algorithms at five different variance levels $($var$=0\mathrm{.}01,0\mathrm{.}05,0\mathrm{.}1,0\mathrm{.}5,1)$ of Gaussian noise $($added to the

image manually$).$ Square root of following relation can be used to compute RMSE.

Where R indicates the number of image rows and C refers to the number of columns, $(,)$ represents

the reference image whereas $(,)$ refers to the image with detected edges using different methods

$($with different variance levels of Gaussian noise$).$ Reference image can be the image with edges using

a Canny Edge detector $($threshold $=0\mathrm{.}1,$ sigma $=1)$ when there is no Gaussian noise.