Biju Patnaik University of Technology 2008-1st Sem B.Tech 8th mage Processing - Question Paper

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Eighth Semester Examination - 2008 IMAGE PROCESSING

Full Marks-70

Time: 3 Hours

Answer Question No. 1 which is compulsory and any five from the rest.

The figures in the right-hand margin indicate marks,

1. Answer the following questions : 2x10

(0 Give ttie mathematical model of a digital image.

(ii) What is variable length coding ?

(fii) What is Weber Ratio ?

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ffv) What fs neighbor of a pixel ? Explain.

(v) What are additive and subtractive colors?

(vi) Differentiate between binary image, grayscale image and color image,

(vfi) How do you measure information ?

(viii) What is quantization error in the context of image processing ?

<ix) Differentiate between histogram equalization and modification.

(x) Explain the terms hue, saturation and intensity.

2. Gray level histogram of ar image is given

below:

Gray Level	C	1	2	3	A	5	6	7
Frequency	400	700	1350	2500	rmi	1500		O

Compute the gray level histogram of the output image obtained by enhancing the input by the histogram equalization technique, to

3 Writ in brief about RGB, CMY, VIQ and HSI colcr models* 10

4/ What do you mean by edge in an image ? Explain how sharpening filter may be used to enhance edges. Also discuss how first and second derivative may be used for detecting edges in an image. 10

5. What are gray level transformations ? Explain

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gray level slicing and contrast stretching, 10

6, In image compression, following mechanisms are used to compress pixel data :

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(i) mapping the pixel values to seme other set of values

(ii) quantizing those va]ues

(iii) symbol encoding the resulting values

Explain each mechanism, Describe how it helps in compressing images. Also describe how it affects the visual quality of the decom-

pressed image when compared with original Image. What are the different quality mea-

sures of compression ?

10

7. Develop a procedure for computing the median of an nxn neighborhood and replace it with the center pixeJ of the image. Repeat it for the entire image of size M xN, Also give a procedure to compute weighted median, i.e. certain pixels are given more weights than others.