MU Computer Engineering (Semester 7)
Image Processing
December 2013
Total marks: --
Total time: --
INSTRUCTIONS
(1) Assume appropriate data and state your reasons
(2) Marks are given to the right of every question
(3) Draw neat diagrams wherever necessary


Justify/Contradict the following statement (any four) :-
1 (a) (i) Unit step sequence is a powersignal
5 M
1 (a) (ii) If the energy of the signal is finite its power is zero
5 M
1 (a) (iii) Brightness discrimination is poor at low levels of illumination
5 M
1 (a) (iv) Enhacement process does not add any information to the image.
5 M
1 (a) (v) All image compression techniques are invertible.
5 M

2 (a) Write an expression for 2-D DFT. What is its relationship with one dimention DFT? How one-dimensional FFT algorithm can be used to compute two dimensional DFT of an digital image.
10 M
2 (b) Define signals and systems and also give any 4 classification of Discrete Time Signals with examples.
10 M

Compare and constrast between the following (any two -)
3 (a) (i) Spatial Domain Processing and Transform Domain Processing.
5 M
3 (a) (ii) Image Enhancement and Image Restoration.
5 M
3 (a) (iii) Lossless and Lossy Compression
5 M
3 (b) Find the DFT of the given image.
[ egin{bmatrix} 0 & 1 & 2 & 1 \ 1 & 2& 3 & 2 \ 2 & 3 & 4 & 3 \ 1 & 2 & 3 & 2 end{bmatrix}]
5 M
3 (c) Find the circular convolution of two sequence -
x1(n)={1,-1,2,-4} and x2(n)={1,2}
5 M

4 (a) Find the universe Z-transform of -
[xleft(z ight)=frac{z^3-4z^2+5z}{left(z-1 ight)left(z-2 ight)left(z-3 ight)}]
(i) ROC=|z|>3
(ii) ROC=|z|<1
ROC=2<|z|<3
10 M
4 (b) What are the different types of redundancies in images.
5 M
4 (c) Explain Fidelity Criteria
5 M

5 (a) Explain filtering in spatial Domain.
10 M
5 (b) Explain segmentation based on discontinuities.
5 M
5 (c) Explain Hough-Transform and its application in detection of shapes.
5 M

6 (a) Explain the salient feature of the following codes :-
(i) Huffman code
(ii) Lossy predictive coding
(iii) Tranform coding.
10 M
6 (b) Explain with suitable example region splitting and merging techniques for segmentation.
10 M

7 (a) Sampling and Quantization.
5 M
7 (b) Edge linking and Boundry detection via graph theoretic technique.
5 M
7 (c) Image Restoration Model.
5 M
7 (d) Trimmed Average filter.
5 M
7 (e) Homomorphic filtering.
5 M



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