A [70 pts). 2-D Optimal Wiener Filtration Comme ths M TUE code Process image len

Question

A [70 pts). 2-D Optimal Wiener Filtration Comme ths M TUE code Process image lena" image by smooth filer plus random noise n (from file 'noise raw) Convol tram i(n, m) (o h)(n, m) +n(n, m), n, m 0 (N 1). N 250. The smooth filter has the point characteristic that h(n, m) for all pixels except the following h(-1 :1.-1:1) Il 21, 232,12 1/15 1. Compute the transfer functions of the smooth Hou) and Wiener filters, Ywin(e), w 2. to the DFT of the degraded image, which is o( )H(w) N Apply the Wiener filter m can be used). 3. Compute errors of blurring, degradation, and filtration (code 'msr error 4a. Display results as shown in Figure 1 r,ur) +0.00011 4b. Display on the next figure two meshes 20 log H (wi,wr) and 20 200,100) for use subplot (2,1 k) and axis Io, 300,0,300 400.00 for k 1, and axis (0300,0300 After computing the blur imase nois image, b and d, you may need to shift cyclically ATLAB code These new images (blur and noisy images) the image; call code "shift LL' o errors. should be used for figures and for computing MSR

Explanation / Answer

Now, you can add these toolboxes to the path.

for translation invariant signal distributions, the Wiener filtering is the optimal filtering.

Perform the wiener filtering

display the filter

isplay the result

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