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b) Similarly to a), we have:  
 
b) Similarly to a), we have:  
  
<math> p_1(e^{jw}) = X(e^{jw},e^{j\nu}) |_{\nu=0} </math>
+
<math> p_1(e^{jw}) = X(e^{jw},e^{j\nu}) |_{\nu=0}</math>
  
 
c) <br>
 
c) <br>
<math> \sum_{n=-\infty}^{\infty} p_0(n) = \sum_{m=-\infty}^{\infty} \sum_{n=-\infty}^{\infty} x(m,n) = X(e^{j\mu}, e^{j\nu}) | {\mu=0, \nu=0} </math>
+
<math> \sum_{n=-\infty}^{\infty} p_0(n) = \sum_{m=-\infty}^{\infty} \sum_{n=-\infty}^{\infty} x(m,n) = X(e^{j\mu}, e^{j\nu}) |_{\mu=0, \nu=0} </math>
 +
which is the DC point of the image.
 +
 
 +
d) No, it can't provide sufficient information.
 +
From the expression in a) and b), we see that <math> p_0(e^{jw}) </math> and  <math> p_1(e^{jw}) </math> are only slices of the DSFT. It lost the information when <math> \mu </math> and <math> \nu </math> are not zero.
 +
A simple example would be:
 +
Let <br>
 +
<math>
 +
x(m,n) =
 +
\left[ {\begin{array}{*{20}{c}}
 +
1 ~ 2 \\
 +
3 ~ 4\\
 +
\end{array}} \right] </math>,
 +
so<br>
 +
<math> p_0(n) =[4~6], p_1(m) =  [3 ~7]^T </math>.
 +
With the above the information of the projection, the original form of the 2D signal cannot be determined. For example,
 +
<math>
 +
x(m,n) =
 +
\left[ {\begin{array}{*{20}{c}}
 +
2 ~ 1 \\
 +
2 ~ 5\\
 +
\end{array}} \right] </math> gives the same projection.
 +
 
 +
Related problem:
 +
Let <math> g(x,y) = sinc(x/2, y/2) </math>, and let <math> s(m,n) = g(mT, nT) </math> where T = 1.
 +
 
 +
a) Calculate <math> G(\mu, \nu) </math> the CSFT of <math>g(x,y) </math>.
 +
 
 +
 
 +
b) Calculate <math> S(e^{j\mu}, e^{j\nu}) </math> the DSFT of <math> s(m,n) </math>.

Latest revision as of 21:48, 10 November 2014

a) Since

$ X(e^{j\mu},e^{j\nu}) = \sum_{m=-\infty}^{\infty} \sum_{n=-\infty}^{\infty} x(m,n)e^{-j(m\mu+n\nu)} $

and

$ p_0(e^{jw}) = \sum_{m=-\infty}^{\infty} \sum_{n=-\infty}^{\infty} x(m,n)e^{-jnw} $, 

we have:

$ p_0(e^{jw}) = X(e^{j\mu},e^{jw}) |_{\mu=0} $

b) Similarly to a), we have:

$ p_1(e^{jw}) = X(e^{jw},e^{j\nu}) |_{\nu=0} $

c)
$ \sum_{n=-\infty}^{\infty} p_0(n) = \sum_{m=-\infty}^{\infty} \sum_{n=-\infty}^{\infty} x(m,n) = X(e^{j\mu}, e^{j\nu}) |_{\mu=0, \nu=0} $ which is the DC point of the image.

d) No, it can't provide sufficient information. From the expression in a) and b), we see that $ p_0(e^{jw}) $ and $ p_1(e^{jw}) $ are only slices of the DSFT. It lost the information when $ \mu $ and $ \nu $ are not zero. A simple example would be: Let
$ x(m,n) = \left[ {\begin{array}{*{20}{c}} 1 ~ 2 \\ 3 ~ 4\\ \end{array}} \right] $, so
$ p_0(n) =[4~6], p_1(m) = [3 ~7]^T $. With the above the information of the projection, the original form of the 2D signal cannot be determined. For example, $ x(m,n) = \left[ {\begin{array}{*{20}{c}} 2 ~ 1 \\ 2 ~ 5\\ \end{array}} \right] $ gives the same projection.

Related problem: Let $ g(x,y) = sinc(x/2, y/2) $, and let $ s(m,n) = g(mT, nT) $ where T = 1.

a) Calculate $ G(\mu, \nu) $ the CSFT of $ g(x,y) $.


b) Calculate $ S(e^{j\mu}, e^{j\nu}) $ the DSFT of $ s(m,n) $.

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood