Image Processing - Dec 2014

Computer Engineering (Semester 7)

TOTAL MARKS: 80
TOTAL TIME: 3 HOURS (1) Question 1 is compulsory.
(2) Attempt any three from the remaining questions.
(3) Assume data if required.
(4) Figures to the right indicate full marks. 1 (a) Explain classification of Discrete systems.(5 marks) 1 (b) Prove that DFT is orthogonal transform.(5 marks) 1 (c) Explain image fidelity criteria.(5 marks) 1 (d) Unit step signal is a power signal. Justify.(5 marks) 2 (a) Check whether the following systems are linear/nonlinear and Time variant/Time invariant.
i) y(n)=e^x(n)
ii) y(n)=n x(n)(10 marks) 2 (b) Find the Z-transforming signals and sketch ROC. [ i) x(n) = left ( dfrac {1}{4} ight )^n u (n) \ ii) x(n) = left ( dfrac {1}{2} ight )^n u(-n-1) ](10 marks) 3 (a) Explain Decimation is time FFT algorithm with signal flow graph.(10 marks) 3 (b) Determine circular convolution of two sequences
x₁(n)={1,2,3,1}
x₂(n)={4,3,2,2}(10 marks) 4 (a) Explain region based image segmentation techniques.(10 marks) 4 (b) Explain image enhancement techniques in spatial domain.(10 marks) 5 (a) Explain various types of redundancies in an image. Specify techniques to remove redundancies.(10 marks) 5 (b) Construct improved gray scale quantization code for given data
{100, 110, 124, 130, 200, 210}(10 marks) 6 (a) Explain trimmed average filtering and median filtering with example.(10 marks) 6 (b) Compute DFT of the given image
(10 marks)

Write short notes on any four:

7 (a) Hough transform(5 marks) 7 (b) Histogram Equalization(5 marks) 7 (c) Wiener filter(5 marks) 7 (d) Noise models(5 marks) 7 (e) Walsh Hadamard Transform.(5 marks)