ROZ2 – cvičení 2 Image restoration - výsledky. Maska gaussiánu function h = gauss(N, sigma) PI = 4*atan(1); npul = (N-1)/2; [x,y] = meshgrid(-1*npul:npul);

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Presentation transcript:

ROZ2 – cvičení 2 Image restoration - výsledky

Maska gaussiánu function h = gauss(N, sigma) PI = 4*atan(1); npul = (N-1)/2; [x,y] = meshgrid(-1*npul:npul); h = 1/(2*PI*sigma^2) * exp(-1*(x.^2 + y.^2)/(2*sigma^2)); h = h / sum(h(:)); gauss(11,5) gauss(21,7)

Poškození obrázku function g = poskod(f, h, SNR) g1 = conv2(f, h); MinI = min(g1(:)); MaxI = max(g1(:)); var_f = var(f(:)); var_n = var_f / 10^(SNR / 10); g = g1 + var_n*randn(size(g1)); g(g<MinI) = MinI; g(g>MaxI) = MaxI;

Výsledky gauss(11,3) gauss(21,7) BSNR 1/

Inverzní filtr function f = inverz(g, h) G = fft2(g); H = fft2(h, size(g,1), size(g,2)); F = G./ H; f = ifft2(F); SNR

Wienerův filtr function f = wiener(g, h, konst) G = fft2(g); H = fft2(h, size(g,1), size(g,2)); R = conj(H)./ (abs(H).^2 + konst); F = R.* G; f = ifft2(F); Gauss(11,3) SNR 60 konst 0,1 0,01 0,001 0,0001

Rozmazání pohybem h = ones(1,10);

Rozmazání pohybem m1 = log(abs(fft2(f).^2)); m2 = real(fft2(m1)); mi = min(m2(:)); m3 = m2 < 0.9*mi; m3 m1 fftshift+výřez

Rozmazání defokusací h =kruh(20,10);

Rozmazání defokusací m1 = log(abs(fft2(f).^2)); m2 = real(fft2(m1)); mi = min(m2(:)); m3 = m2 < 0.9*mi; fftshift(m3)fftshift(m1)