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Filtering
(i) Write an m-file "mymedian.m" which will take an image and filter size and perform median filtering. Display input and output image. Use
help median
function imm=mymedian(imn,msize) [h w]=size(imn); kernel_size=? imm=imn; for i=msize+1:(h-msize) for j=msize+1:(w-msize) imm(i,j)=median(reshape(imn(i-msize:i+msize,j-msize:j+msize),1,kernel_size)); end end
What is the median value of an image?
Comment on the complexity (number of operations per pixel) of the algorithm.
(ii) Write an m-file "mygaussian.m" which will take an image and filter size and perform Gaussian filtering. Display input and output image.
function img=mygaussian(imn,sigma) g=gauss(sigma);
img=?(iii) Perform median and Gaussian filtering on face_g.png, face_m.png,statue_m.png. What kind of noise the median filer is useful for? What kind of noise the Gaussian filer is useful for?
Now that you have the input and output impedances you can design the matching networks. I will require either the Smith Charts showing how you calculated the matching components or
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power factor improvement
An arrangement of Windows so every window is neatly stacked with only the title bar of every window is showing.
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