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{\plain {Image Restoration with the Parametric
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{0:Np}NAME~20
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{0:G}NAME({0:\m}NAME,{0:\s}NAME,{0:x}NAME)~{0:if}NAME(|({0:x}NAME-{0:\m}NAME)<3*{0:\s}NAME,({0:e}NAME)^(-((((({0:x}NAME-{0:\m}NAME))^(2))/((2*{0:\s}NAME*{0:\s}NAME))))),0)
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{\plain {The image, f(x,y), has been blurred
 by H(u,v) and corrupted by additive white
 noise of power Pn.}}
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.EQN 5 4 6 0
({0:H}NAME)[({0:i}NAME,{0:j}NAME):{0:G}NAME({0:\m}NAME,{0:\s}NAME,({0:u}NAME)[({0:i}NAME))*{0:G}NAME({0:\m}NAME,{0:\s}NAME,({0:v}NAME)[({0:j}NAME))
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.EQN 1 -54 21 0
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0 2 5 0 NO-TRACE-STRING
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{\plain Filter transfer function}
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{\plain {The Parametric Wiener Filter}}
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{\plain {In this example the noise dominates
 the entire upper half of the spectrum, 
but the blurring is not excessive.\par The
 paremeters k, N and }{\f1 s}{ permit modeling
 the signal and noise spectra and the blurring
 MTF, respectively, \par and }{\f1 g}{ controls
 the degree of restoration.}}
}