Digital Signal and Image Processing (DSIP) Semester 7 (3 Hours) December 2013

Digital Signal and Image Processing (DSIP) Semester 7 (3 Hours) December 2013
LJ-13993 [Total Marks : 100]
N.B:	(1)	Question no 1 is compulsory.
	(2)	Attempt any four question out of remaining six questions.
	(3)	Assume suitable data wherever necessary and state them properly.
1.	Justify/Contradict the following statements (any four) :-		20
	(a)	Unit step sequence is a power signal.
	(b)	If the energy of the signal is finite its power is zero.
	(c)	Brightness discrimination is poor at low levels of illumination.
	(d)	Enhancement process does not add any information to the image.
	(e)	All image compression techniques are invertible.
2.	(a)	Write an expression for a 2-D DFT. What is its relationship with one dimension DFT? How one-dimensional FFT algorithm can be used to compute two dimensional DFT of an digital image.	10
	(b)	Define signals and systems and also give any 4 classification of Discrete Time Signals with examples.	10
3.	(a)	Compare and contract between the following (any two) :-      (i) Spatial Domain Processing and Transform Domain Processing.      (ii) Image Enhancement and image Restrocation.      (iii) Lossless and Lossy Compression.	10
	(b)	Find the DFT of the given image.   [ 0 1 2 1 1 2 3 2 2 3 4 3 1 2 3 2 ]	05
	(c)	Find the circular convolution of two sequences -      x1(n) = {1, - 1,2-4} and x2(n) = {1,2}	05
4.	(a)	Find the universe Z-transform of-     x(z) = Z3 - 4z2 + 5z / (z-1) (z-2) (z-3) (i)     ROC = |Z| > 3 (ii)    ROC = |Z| <1 (iii)   ROC = 2 < |Z| <3	10
	(b)	What is the difference types of redundancies in images.	05
	(c)	Explain Fidelity Criteria.	05
5.	(a)	Explain filtering in spatial Domain.	10
	(b)	Explain segmentation based on discontinuities.	05
	(c)	Explain Hough - Transform and its application in detection of shapes.	05
6.	(a)	Explain the salient feature of the following codes :-    (i) Huffman code    (ii) Lossy predictive coding    (iii) Transform coding   x(z) = Z3 - 4z2 + 5z / (z-1) (z-2) (z-3)	10
	(b)	Explain with suitable example region splitting and merging techniques for image segmentation.	10
7.	write short notes on (any four) :-		20
	(a)	Sampling and Quantization
	(b)	Edge linking and Boundary detection via graph theoretic technique.
	(c)	Image Restoration Model.
	(d)	Trimmed Average filter.
	(e)	Homomorphic filtering.