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2003 Course Digital Image Processing

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Total No. of Questions : 12] P1478 [Total No. of Pages : 2 [3764] - 234 B.E. (E & TC) DIGITAL IMAGE PROCESSING (2003 Course) Time : 3 Hours] [Max. Marks : 100 Instructions: 1) Answer any three questions from each section. 2) Answers to the two sections should be written in separate books. 3) 4) Neat diagrams must be drawn wherever necessary. Assume suitable data, if necessary. SECTION - I 1 ) a) b) 2 ) a) b) 3 ) a) b) 4 ) a) b) Briefly explain the following. i) Brightness adaptation. ii) Simultaneous Contrast. What is false contouring? Explain. [8] [8] OR With the help of block diagram explain monochrome vision model of [8] human eye. Explain Mach band effect. [8] Explain KL transform with its properties. Give applications of KL transform. [8] Explain DCT. Why DCT is preffered in JPEG Compression compared to other transform. [8] OR Write equation for 2D Hadamard transform and give the basis image for N=4 [8] Explain following properties of 2D fourier transform. i) Translation. ii) Rotation. iii) Periodicy. iv) Symmetry. [8] P.T.O. 5) a) b) 6 ) a) b) 7 ) a) b) Explain wiener filtering. Give its advantages over inverse filtering. [9] Explain HSI color model. Give its advantages and applications. [9] OR Explain edge detection for color image. [9] What is image restoration? How it differes from image enhancement.[9] Explain JPEG compression standard. [10] 4 4 image is represented by following matrix. Determine entropy of the image. Give huffman coding table. 8) ) b) 9) ) b) 10) ) b) 11) ) b) 12) ) b) 2 4 8 2 4 4 8 8 8 4 8 8 4 4 4 4 [6] OR With the help of block diagram explain transform coding. Explain bit plane coding. [8] [8] What is boundary representation? Explain how chain codes are used for boundary representation. [8] With the help of appropriate masks explain the following. i) Point detection. ii) Line detection. iii) Edge detection. [8] OR Explain edge detection procedure using sobel mask. Discuss the problems [8] in presence of noise. Explain edge linking using Hough transform. [8] Explain median filtering and average filtering. Give its applications. Compare median filter with averaging filter. [9] A gray level transform is given by T (i) = ai +b. Where i is the original gray value. What are transform coefficients (a&b) if we are inverting image. Give applications of image inversion (negation). [9] OR Explain Homomorphic filter. [9] What is Laplacian? Explain the use of laplacian for enhancement. [9] [3764] - 234 ***** -2-

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