5 Years Integrated M.Sc.(IT)(Semester - 7) 060010707 Digital Image Processing UNIT 1 Introduction to Image Processing Q: 1 Answer in short. 1. What is digital image? 1. Define pixel or picture element? 2. Why do we need digital image processing? 2. Give name of any three related fields of digital image processing. 3. How image analysis defers from digital image processing? 4. What do you mean by low level processing in image processes? List any two such processes. 5. Which operations are performed in mid level image processes? List any two such processes. 3. Give any five reasons for popularity of digital image processing. 4. List phases of digital image processing. 5. What is goal of image enhancement? 6. How does image enhancement is defers from image restoration? 7. What is the purpose of morphological processing? 8. Specify the elements of DIP system. 9. What is meant by illumination? 10. Why there is need for GPU? 11. Define computer vision. 12. Which frequency band used by MRI technology? 13. What is represented by f in image f(x, y)? 14. Which is the image processing technique used to improve the quality of image for human viewing? 15. What is goal of image compression? 16. Give any two applications of computer vision. Q: 2 Answer following questions in detail. 1. Explain fundamental steps in image processing. 2. Explain the usage of digital image processing in medical field. 3. Distinguish between analog image and digital image. Give suitable example. 4. Describe the functions of elements of digital image processing system with a diagram. 5. How image is get converted into digital image? 6. Differentiate between digital image processing and computer vision with example. 7. Explain application of imaging which uses: a. Gamma-Rays b. X-Ray c. Ultraviolet d. Visible and Infrared band e. Microwave band f. Radio band 8. Write a note on computer vision. Does it require image processing? 9. Summarize the application of digital image processing in society. 10. Can digital image processing able to play role in enhancing security of our nation? How? 11. Calculate storage requirement in memory (in KB) for following images: Image Resolution No of Colors 512 X 512 2 1024 X 1024 8 512 X 1024 RGB 1024 X 2048 16 Jitendra Nasriwala Page 1
UNIT 2 Digital Image Fundamentals and Operations 1. What do you mean by sampling & quantization? 2. What is intensity resolution? How do you measure it? 3. What is spatial resolution? How do you measure it? 4. What do you mean by bit depth? What is bit depth of binary image? 5. What do you mean by dynamic range of an image? Give dynamic range of binary image. 6. Which effect caused by because of low intensity resolution? 7. Define interpolation. Give any three advantages of interpolation. 8. Calculate storage requirements of 8-bit image with size 128 X 128. 9. Calculate storage requirements of image with size 128 X 128 and 64 gray levels. 10. Give any three names of image editing tools which make use of interpolation. 11. Define 4-neighbor of a pixel. 12. Define 8-neighbor of a pixel. 13. If points (x-1, y-1), (x+1, y+1), (x-1, y+1), (x+1, y-1) are neighbors of pixel p(x, y), identify type of relationship? 14. Justify N4(P) U ND(P) = N8(P). 15. Define following adjacency: a. 4-adjacency b. 8-adjacency c. m-adjacency 16. Define path/curve. What are 4-path, 8-path and m-path? 17. Define connectivity. 18. What do you mean by connected component and connected set? 19. How do you identify two regions are adjacent? 20. Define border. How do you identify border if subset of image is image itself? 21. How array operation differs from matrix operation? 22. What do you mean by linear and nonlinear image operations? 23. Give any two example applications of image arithmetic. 24. Give any two example applications of image logical operations. 25. Which image operation is used in masking? 1. What makes image quality better, spatial resolution or intensity resolution? Justify your answer. 2. What will be the effect on image storage size for different spatial resolution and intensity resolution? 3. How one can decides on what will be the spatial and intensity resolution for improving image quality? 4. Justify your answer: Higher spatial resolution leads to higher image quality. 5. Justify your answer: Higher intensity resolution leads to higher image quality. 6. What is an interpolation? Describe nearest neighbor interpolation. Also describe how it can be applied to digital image. 7. Explain bilinear interpolation with example. 8. Describe bicubic interpolation. How it is better than bilinear interpolation? 9. Define different types of neighbor relationship with its notations and example. 10. Define different types of distance measures with example. 11. Prove with example that max operation on image is non-linear. 12. Prove with example that sum operation on image is linear. 13. Explain each of the four image arithmetic operations with one example applications. 14. Consider the image segment shown below and answer the next questions: *4 4 0 3 3 0 0 4 3 0 3 2 3 3 0 3 4 0 0 4 3 2 0 3 4 1 4 3 4 0 1 1 4 2 1 0 0 2 3 3 4 0 2 3 2 0 1 1 1 1 0 4 0 0 0 2 Jitendra Nasriwala Page 2
0 2 2 1 2 1 0 0 3 2 4 0 1 0 2 4 a. Identify intensity set of N4P(4, 4), N8P(7, 4), NDP(5,6). b. Consider V = {2, 3, 4}, Identify pixel P(3, 4) and q (2, 4) are in 4 adjacency? c. Consider V = {2, 3, 4}, Identify pixel P(3, 4) and q (2, 5) are in 8 adjacency? d. Consider V = {0, 1}, Identify pixel P(4, 8) and q (3, 7) are in mixed adjacency? e. Consider V = {0, 1, 2}, find shortest 4 path, 8 path and m path between pixel p(1, 1) to p(9, 6). Also give its length. f. Consider V = {0, 1}, find shortest 4 path, 8 path and m path between pixel p(8, 8) to p(1, 6). Also give its length. g. Consider two subset s1 and s2 as red and blue colored pixels in image respectively. Identify whether the s1 and s2 are 4- adjacent for V={1, 2}? h. Consider two subset s1 and s2 as red and blue colored pixels in image respectively. Identify whether the s1 and s2 are 8- adjacent for V={3, 4}? i. Identify Euclidian, city block and chessboard distance between point P1(6, 2) and P2(5, 6). UNIT 3 Image Enhancement in Spatial Domain 1. How spatial domain image processing techniques are differs from transform domain? 2. What are the two principal categories of spatial processing? 3. How many pixels considered in intensity transform functions operation? 4. In spatial filtering, if size of neighborhood is 1 X 1 what it called? 5. Define thresolding function. 6. What do you mean by dynamic range in an image? 7. How can you convert a gray scale image into binary image? 8. Give expression for image negative. 9. List any two applications of image negative. 10. State the purpose of log transform in image processing. 11. What do you mean by gamma correction? Where it is used? 12. Give any two application of power law transformation. 13. What is the advantage of piecewise linear functions? 14. What is the major disadvantage of piecewise linear functions? 15. Define histogram of an image. 16. What do you mean by clipping piece wise linear function. 17. What are the four types of image based on intensity characteristics? 18. What do you mean by local and global histogram processing? 19. What is kernel in spatial filtering? 20. What do you mean by w(x, y) f(x, y) and w(x, y) * f(x, y)? 21. Why smoothing filter also known as averaging filter? 22. Give any two characteristics of smoothing linear filters. 23. Give general form of weighted averaging filter. 24. Give advantage of median filter. 25. What is the result/conclusion of applying first order derivative to image data? 26. What is the result/conclusion of applying second order derivative to image data? 27. List different types of Laplacian masks found in practice. 28. What is directional smoothing? 29. What is conservative smoothing? 1. Explain any two intensity transformation function with example, characteristics graph and at-least two applications. 2. Consider image with 16 grey level given in figure 3.1. Perform digital negative operation on it. Show result image data. 3. What do you mean by piece wise linear image operations? Explain any two such operations. 4. What s a main goal of contrast stretching? In what situation it is useful. Explain contrast stretching with example. 5. How intensity slicing is defers from bit-plane slicing? Give at-least two example of each. Jitendra Nasriwala Page 3
6. What is histogram? How does histogram help to identify type of image based on intensity characteristics? 7. Write a note on advantages of Histogram. 8. Explain the process of histogram equalization. 9. Perform histogram equalization given for 8 X 8 image data shown in below table. Grey Level (r1) 0 1 2 3 4 5 6 7 Number of Pixels (Pk) 8 10 10 2 12 16 4 2 10. Explain the mechanics of spatial filtering? 11. Explain spatial correlation and convolution with example. 12. Write a note on averaging filters. 13. Explain the effect of neighborhood size on image for smoothing filters. 14. Discuss the effect of averaging filters on an image. Also Give application of averaging filters. 15. Apply standard smoothing filter to following image data (calculate only for highlighted pixels). 14 12 11 10 12 9 12 13 11 4 8 14 10 12 12 11 Figure 3.1 16. Apply weighted smoothing filter to above given image data (calculate only for highlighted pixels). 17. Perform bit-plane sizing on 2 nd bit for the image given in Figure 3.1. 18. What is intensity slicing? Perform intensity slicing on image data for intensity 5 to 10 given in Figure 3.1. 19. An image is in the range 10-50. To display the image on a device that has the grey level range 0-255, what is the linear transformation that is required? Also identify new value for intensity 12, 30, 40 and 49. 20. Explain how second order derivative is used to sharpen an image. 21. Explain the results of unsharp masking and highboost filtering. UNIT 4 Image Segmentation 1. What is segmentation? 2. Why segmentation is important for image processing applications? 3. What is ROI? 4. Give any one example of manual and semi manual segmentation. 5. How isolated point can be detected? 6. What is the significant of Threshold value in identifying point discontinuity? 7. Write mask for vertical line detection. 8. Write names of different types of edges. 9. Give function for finding first derivative. 10. What is localization in edge detection? 11. Give mask for Roberts operator. 1. What are the characteristics of segmentation process? 2. Write a note of classification of image segmentation algorithm. 12. Write note on line detection. 3. What is edge? Explain various stages of edge detection. 4. Consider a one dimensional image f(x)= 60 60 60 60 100 100 100 100 50 100 100 10 15 20 25 30 35 40 45 200. What are the first and second derivatives? Locate the position of edge. 5. Write a note on Roberts operator. 6. Derive Prewitt and Sobel operators mask. Jitendra Nasriwala Page 4
7. Derive second order derivative mask. 8. Apply laplacian mask on image data given in figure 3.1. Jitendra Nasriwala Page 5
UNIT 5 Image Morphology 1. What is the role of morphology in image processing? 2. Which tool is used for analyzing the shapes of the objects present in images? 3. What is structuring element? 4. Give any three common structuring elements. 5. What are composite structuring elements? 6. What are elementary structured mask? 7. What are the elements of basic morphological structuring elements? 8. Give two basic morphological operator names. 9. How erosion and dilation can be obtained using median filter? 10. What is boundary extraction? 11. What is the difference between outlining and boundary? 12. What is the difference between thinning and thickening? 13. What is impulse noise? Can morphological operation used to remove it? 14. How morphological operation used to remove salt and pepper noise? 1. What are the multiple ways of finding dilation and erosion for binary image? 2. The combined operation of erosion followed by dilation is called an opening operation. Are not these operations the reverse of each other and hence restore the original image? Justify. 3. Explain the algorithm for dilation and erosion. 4. Perform erosion and dilation for image A given in below figure and structuring element be [ 1 1 ]. 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 Image 5.1 5. Consider following structuring elements s1 and s2 and perform erosion and dilation. 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 0 S1 S2 6. What is fit, hit and miss? How it is used to modify dilation and erosion algorithm? Explain with example image. 7. Write a note on properties of erosion and dilation. 8. What is opening and closing operations? What are its applications? 9. What is hit-or-miss transform? Explain its applications. 10. How morphological operation used to extract boundary? Explain. 11. What is thinning and thickening? How it can be obtained using morphological operations? Give its applications. 12. What is convex hull? How it can be obtained using morphological operations? Give its applications. 13. Write a note on skeletonization. 14. Write a note on watershed algorithm. Jitendra Nasriwala Page 6