Review Problems for Midterm Examination: CS474/674



 1. Draw a piecewise linear transformation that takes [0,39] to 0,
    [40,200] to [0,255] and [201, 255] to 255.

 2. How can the contrast of an image be increased by using XView or
    LView Pro or Matlab? Give complete directions.

 3. If we wanted high compression to yield a much smaller image file,
    what format should we use to save an image? What are its disadvantages?

 4. If we wanted to compress an image but wanted to keep the same level of
    detail, what formats could we use for saving an image?

 5. What determines the resolution of an image when a very high resolution
    image is scanned into digital form? What does the value of each pixel 
    value represent in terms of the original image?

 6. If we use 8-bits for each pixel value for a color image, then what
    do the pixel values represent in terms of colors and the R, G and B
    values for the color guns for displaying the image on a video monitor?

 7. Why is it so convenient to process gray scale images in the PGM format?

 8. What does a histogram of a gray scale image tell us about an image that
    has a bad distribution of gray levels?

 9. What is the purpose of histogram equalization?

10. Suppose that you want to use LView Pro to filter an image with a
    convolution mask. Describe how to do it, once the image is loaded
    into LView Pro's workspace.

11. What is the JPEG image format good for?

12. Derive a mask for unsharp masking by adding two masks and give the
    purpose of each of the two masks.

13. Design a 5x5 mask that detects edge pixels going in a diagonal
    direction from the lower left to the upper right.

14. Design a 5x5 mask that will detect edge or line pixels moving in
    either direction along a line from the upper right to the lower
    left corners.

15. Draw a 3x3 mask and a 3x3 nbhd of a pixel. Give the mathematical
    equation for the mask convolution of these two 3x3 blocks.

16. Design an algorithm that smooths pixels that have very different
    values from the average value of the other nbhd pixels, but
    otherwise does not change the pixel value.

17. Desing a blurring mask that blurs moderately but not strongly.

18. Suppose we want to use the Laplacian convolution mask on an image
    (all -1 values except for the value 8 in the center). What could we
    do first to help keep it from accentuating the noise?

19. Describe how to do unsharp masking on the image "shuttle.pgm" by
    use of either the tool <I>LView Pro</I> or <I>Matlab</I>.

20. If we load a PGM image into a text editor, how can we tell if it
    is in packed format or not?

21. Draw a thresholding graph for a transformation that will segment 
    an image into regions of 5 separate gray scales.

22. Describe an algorithm in psuedo-code that will do the thresholding
    of an image into 5 separate gray levels (only the critical part
    where the thresholding is done).

23. Describe an algorithm that selects a pixel at random, and then
    grows a connected region around it consisting of all pixel values
    that are quite close to its value.

24. In Problem 23 above, what would cause the region to quit growing?

25. Write the pseudo-code for an algorithm that examines each pixel
    in an image and computes the 8 differences of the other 8 pixels
    in its 3x3 nbhd. If the average difference magnitude is greater 
    than 12, then change output center pixel value to have a greater
    difference, else put the output center pixel value to be equal
    to the average value.

26. Does the process in Problem 25 above smooth or sharpen an image?

27. What is the net result if an image is converted to its negative
    and then added to the original image (addition is on each pixel)?

28. What is the net result if an image is added to itself and truncated
    so that the output sum pixel values are truncated to [0, 255]?

29. Give examples of 3x3 convolution masks that smooth and sharpen.

30. Give examples of 3x3 convolution masks that detect edges moving
    along horizontal and vertical lines, moving left or right, or
    moving up or down (both directions on each line). Give an example
    of a mask that will detect edges in all directions (there are 8
    directions, total).