Question: Edge detection methods are often compared by their ability to detect edges in noisy images. Let us perform the Prewitt operator on the Lenna

Edge detection methods are often compared by their ability to detect edges

Edge detection methods are often compared by their ability to detect edges in noisy images. Let us perform the Prewitt operator on the Lenna image with additive Gaussian noise. Add noise to the test image and extract its edges. imnoise (I, 'gaussian'); I_noise edge (I_noise, 'prewitt'); subplot (2,2,3), imshow (I_noise), title('Image w/ noise'); subplot (2,2,4), imshow (I_prw2), title ('Prewitt on noise'); [I_prw2, t2] = 1. How did the Prewitt edge detector perform in the presence of noise (compared to no noise)? 2. Did MATLAB use a different threshold value for the noisy image? 3. Try using different threshold values. Do these different values affect the operator's response to noise? How does the threshold value affect the edges of the object?

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