%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Averaging demo S = zeros(100,100); S(40:60,40:60) = 1; imagesc(S) N = .1*randn(100,100); imagesc(N) I = S+N; imagesc(I) A = fspecial('average', 3) O = conv2(A,I); imagesc(O) A = fspecial('average', 9) O = conv2(A,I); imagesc(O) % Filtering and structure G = fspecial('gaussian', 9, .5); imagesc(conv2(G,I)) G = fspecial('gaussian', 9, 1.5); imagesc(conv2(G,I)) G = fspecial('gaussian', 9, 3); imagesc(conv2(G,I)) G = fspecial('gaussian', 18, 6); imagesc(conv2(G,I)) G = fspecial('gaussian', 36, 12); imagesc(conv2(G,I)) G = fspecial('gaussian', 9, .5); imagesc(conv2(G,dogbw)) G = fspecial('gaussian', 9, 1.5); imagesc(conv2(G,dogbw)) G = fspecial('gaussian', 9, 3); imagesc(conv2(G,dogbw)) G = fspecial('gaussian', 18, 6); imagesc(conv2(G,dogbw)) G = fspecial('gaussian', 36, 12); imagesc(conv2(G,dogbw)) % Subsampling A = zeros(100,100); for i = 40:41 for j = 10:90 A(i,j) = 1; end, end B = imrotate(A, 30); imagesc(B) imagesc(B(1:4:100,1:4:100)) G = fspecial('gaussian', 9, 3); C = conv2(G,B); imagesc(C) imagesc(C(1:4:100,1:4:100))