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d) Sketch a chromaticity diagram and plot and label the following on it:
 
d) Sketch a chromaticity diagram and plot and label the following on it:
<math>1. (x,y)=(1,0)\\
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2. (x, y) = (0,1)</math>\\
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<math>
3. (x, y) = (0,0)</math>\\
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  \\
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1. (x,y)=(1,0)\\
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2. (x, y) = (0,1)\\
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3. (x, y) = (0,0)\\
 
  4. (R,G,B) = (255, 0 , 0)\\
 
  4. (R,G,B) = (255, 0 , 0)\\
 
  5. (R, G, B) = (0, 255,0)\\
 
  5. (R, G, B) = (0, 255,0)\\
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e) Imagine that the values of <math>(R,G,B)</math> are quantized to 8 bits, and that you view a smooth gradient from black to white on this device. What artifact are you likely to see, and where in the gradient will you see it?
 
e) Imagine that the values of <math>(R,G,B)</math> are quantized to 8 bits, and that you view a smooth gradient from black to white on this device. What artifact are you likely to see, and where in the gradient will you see it?
  
:'''Click [[QE637_T_Pro1|here]] to view student [[QE637_T_Pro1|answers and discussions]]'''
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:'''Click [[CS5_2015_Aug_prob1|here]] to view student [[CS5_2015_Aug_prob1|answers and discussions]]'''
 
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===Part 2===
 
===Part 2===
  
Consider the following 2-D LSI systems. The first system has input <math>x(m,n)</math> and output <math>y(m,n)</math>, and the second system has input <math>y(m,n)</math> and output <math>z(m,n)</math>.
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Consider an X-ray imaging system shown in the figure below. <br />
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[[ Image:Pro2_2015_Aug.PNG ]]<br />
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Photons are emitted from an X-ray source and columnated by a pin hole in a lead shield. The columnated X-rays then pass in a straight line through an object of length T with density u(x) where x is the depth into the object. The number of photons in the beam at depth <math>x</math> is denoted  by the random variable <math> Y_x</math> with Poisson density given by
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<math>
 
<math>
y(m,n) = \sum\limits_{j =  - N}^N {{a_j}x(m,n - j)} \quad\quad S1</math> <br \>
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P\{Y_x = k\} = \frac{e^{-\lambda_x}{\lambda}^{k}_{x}}{k!} .
<math>z(m,n) = \sum\limits_{i =  - N}^N {{b_i}y(m-i,n)} \quad\quad S2</math>
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</math>
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 +
Where x is measured in the units of <math>cm</math> and <math>\mu(x)</math> is measured in units of <math>cm^{-1}</math>.
  
a) Calculate the 2-D impulse response, <math>h_1(m,n)</math>, of the first system.
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a) Calculate the mean of <math> Y_x</math>, i.e. <math>E[Y_x]</math>.
  
b) Calculate the 2-D impulse response, <math>h_2(m,n)</math>, of the second system.
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b) Calculate the variance of <math> Y_x</math>, i.e. <math>E[(Y_x-E[Y_x])^2]</math>.
  
c) Calculate the 2-D impulse response, <math>h(m,n)</math>, of the complete system.
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c) Write a differential equation which describes the behavior of <math>\lambda_x</math> as a function of <math> x</math>.
  
d) How many multiplies does it take per output point to implement each of the two individual systems? How, many multiplies does it take per output point to implements the complete system with a single convolution.
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d) Solve the differential equation to form an expression for <math>\lambda_x</math> in terms of <math>\mu(x)</math> and <math>\lambda_0</math>.
  
e) Explain the advantages and disadvantages of implementing the two systems in sequence versus a single complete system.
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e) Calculate an expression for the integral of the density, <math> \int_{0}^{T} \mu dx </math>, in terms of <math>\lambda_0</math> and <math>\lambda_T</math>
  
:'''Click [[QE637_T_Pro2|here]] to view student [[QE637_T_Pro2|answers and discussions]]'''
+
:'''Click [[CS5_2015_Aug_prob2|here]] to view student [[CS5_2015_Aug_prob2|answers and discussions]]'''
  
 
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[[ECE_PhD_Qualifying_Exams|Back to ECE QE page]]:
 
[[ECE_PhD_Qualifying_Exams|Back to ECE QE page]]:

Latest revision as of 11:53, 7 December 2015


ECE Ph.D. Qualifying Exam

Communication, Networking, Signal and Image Processing (CS)

Question 5: Image Processing

August 2015



Part 1

Consider the emissive display device which is accurately modeled by the equation

$ \left[ {\begin{array}{*{20}{c}} X\\ Y\\ Z \end{array}} \right] = \left[ {\begin{array}{*{20}{c}} a&b&c\\ d&e&f\\ g&h&i \end{array}} \right]\left[ {\begin{array}{*{20}{c}} R\\ G\\ B \end{array}} \right] $

where R, G and B are the red, green, and blue inputs in the range 0 to 255 that are used to modulate physically realizable color primaries.

a) What is the gamma of the device?

b) What are the chromaticity components $ (x_r,y_r), (x_g,y_g) $ and $ (x_b,y_b) $ of the device's three primaries.

c) What are the chromaticity components $ (x_w,y_w) $ of the device's white point.

d) Sketch a chromaticity diagram and plot and label the following on it:

$ \\ 1. (x,y)=(1,0)\\ 2. (x, y) = (0,1)\\ 3. (x, y) = (0,0)\\ 4. (R,G,B) = (255, 0 , 0)\\ 5. (R, G, B) = (0, 255,0)\\ 6. (R,G,B) = (0, 0, 255) $

e) Imagine that the values of $ (R,G,B) $ are quantized to 8 bits, and that you view a smooth gradient from black to white on this device. What artifact are you likely to see, and where in the gradient will you see it?

Click here to view student answers and discussions

Part 2

Consider an X-ray imaging system shown in the figure below.
Pro2 2015 Aug.PNG
Photons are emitted from an X-ray source and columnated by a pin hole in a lead shield. The columnated X-rays then pass in a straight line through an object of length T with density u(x) where x is the depth into the object. The number of photons in the beam at depth $ x $ is denoted by the random variable $ Y_x $ with Poisson density given by

$ P\{Y_x = k\} = \frac{e^{-\lambda_x}{\lambda}^{k}_{x}}{k!} . $

Where x is measured in the units of $ cm $ and $ \mu(x) $ is measured in units of $ cm^{-1} $.

a) Calculate the mean of $ Y_x $, i.e. $ E[Y_x] $.

b) Calculate the variance of $ Y_x $, i.e. $ E[(Y_x-E[Y_x])^2] $.

c) Write a differential equation which describes the behavior of $ \lambda_x $ as a function of $ x $.

d) Solve the differential equation to form an expression for $ \lambda_x $ in terms of $ \mu(x) $ and $ \lambda_0 $.

e) Calculate an expression for the integral of the density, $ \int_{0}^{T} \mu dx $, in terms of $ \lambda_0 $ and $ \lambda_T $

Click here to view student answers and discussions

Back to ECE QE page:

Alumni Liaison

Recent Math PhD now doing a post-doctorate at UC Riverside.

Kuei-Nuan Lin