IMAGE PROCESSING [ELECTIVES] MAY 2012 ELECTRONICS AND TELECOMMUNICATION SEMESTER 8

IMAGE PROCESSING [ELECTIVES] MAY 2012 ELECTRONICS AND TELECOMMUNICATION SEMESTER 8

Con. 4479-12.                         (REVISED COURSE)                                        GN-8375
                                                      (3 Hours)                                          [Total Marks : 100]

N. B. : (1) Question No. 1 is Compulsory.
           (2) Attempt any four questions out of remaining six questions.
           (3) Figures to the right indicate full marks.

1.	Justify the following statements :-	20
	(a) Poorly illuminated images cannot be easily segmented.
	(b) The median filtering perfoms well in images corrupted by impulse noise.
	(c) If kernel of an binze transform is seperable and symmetric, the transform
	can be expressed in matrix form.
	(d) The first derivate of chain code mormalize it to rotation.
	(e) the entropy of an image is maximized by histogram equalization.
2. (a)		6
	length N. Show that N2 orthogonal patterns (basic images) of size N x N
	can be generated using the sequences. Prove the orthogonality of
	these patterns.
(b)	Write first four Hass sequences of length N =4, using these sequences	6
	generate 16 orthogonal Hass patterns.
(c)	Using folloowing three orthogonal sequences show that 9 orthogonal	8
	patterns of size 3 x 3 can be generated. Give all patterns.
3. (a)	What is histogram of a digital image ? What information one can get by	8
	observing the histogram of images ?
(b)	Histogram of a digital binze with eight quantization level is given below.	12
	Perform histogram equalisation. Derive the transformation function
	and new histogram.
4. (a)	Write 8 x 8 Harr matrix and prepare butterfly diagram to compute Harr	10
	coeffcidents of a sequence of length n = 8.
(b)	Using above diagram compute Harr cofficidents of the following sequence.	10
	f(x) = {1 2 3 4 4 3 3 1}
	Evaluate the energy in each of the transform cofficidents.
5. (a)	What is 2-DDFT ? State the properties of DFT matrix applicable to	6
	images.
(b)	Write the expression for 1-D and 2-D. Discrete cosine transform.	6
	State its usefulness in image processing.
(c)	Obtain 2-D DFT of following 3 x 3 image.	8
6. (a)	What is image compression ? Explain different types of reduncies.	6
(b)	Explain the basic principle of transform coding for image compression and	7
	illustrate the save with the help of Discrete Fourier Transform (DFT) and
	Discrete Cosine Transform (DCT).
(c)	Find a set of code words and average word length using Hoff man coding	7
	scheme with symbol having different probabilities as given.
7.	Write short notes on :-	20
	(a) Texture analysis
	(b) Fourier Descriptors
	(c) Image Restoration
	(d) K-L transform
	(e) Moments.