Thursday, July 3, 2014

Digital Signal and Image Processing (DSIP) Semester 7 (3 Hours) December 2010

Digital Signal and Image Process

Digital Signal and Image Processing (DSIP)
Semester 7
(3 Hours) December 2010

 

GT-8844
[Total Marks : 100]
 

N.B: (1) Question no 1 is compulsory.  
  (2) Attempt any four out of remaining six questions.  
  (3) Figures the right indicate full marks.  
       
1. Justify the following statements. (any four) 20
  (a) If the kernel of the image transform is separable and symmetric the transform can be explained in matrix form.  
  (b) Laplacian is not good edge detector.  
  (c) Lossy compression is not suitable for compressing executable files.  
  (d) Low pass filter is a smoothing filter.  
  (e) Unit step sequence is a power signal  
       
2. (a) List and prove any four properties of DFT 10
  (b) Find the circular convolution on the given two sequence x1(n) = {1,-1, 2, -4}
   x2(n) = {1, 2}.
05
  (c) Compute the Hadamard of the image shown
 
2 1 2 1
1 2 3 2
2 3 4 3
1 2 3 2
05
       
3. (a) Give the classification of noice in images. Compare restoration and enhancement. 10
  (b) Three column vector are given below. Show that they are orthogonal. Also generate all possible patterns.
X1 = [1 1 1 ] X2 = [-2 1 1 ] X3 = [0-1 1].
10
       
4. (a) Equalize the given Histogram. What happens when we equalize it twice? Justify.
 
Grey Level 0 1 2 3
Number of pixels 70 20 7 3
10
  (b) Explain image segmentation using thresholding. How to apply thresholding to unevenly illuminated images. 10
     
5. (a) Explain log transformation. How is gamma correction done. 10
  (b) Determine the Z-transform of the following discrete time signals and also specify the region of convergency(ROC).
(i)  x(n) = {1, 2, 3, 4}
           

(ii)
x(n) = {1, 3, 5, 7}
             ↑
(iii) x(n) = {1, 2, 3, 4, 5, 6, 7}
10
       
6. (a) Find the Huffman code for the following stream of data (28 point).
  {1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6, 6, 7}.
10
  (b) What do you mean by Gaussian noise and why is avergians filter used to eliminate it? 05
  (c) List down the advantages and disadvantages of Wiener filter. 05
       
7. Write shortnotes (any two) :- 20
  (a) KL Transform.  
  (b) JPEG compression  
  (c) Hough Transform  
  (d) Classification of signals.  

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