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Unformatted text preview: 1 EE 211A Digital Image Processing I Fall Quarter, 2010 Handout 19 Instructor: John Villasenor Computer Assignment 3 Image Enhancement Due: Thursday, 18 November 2010 What to turn in: 1. A statement of the fraction of energy located at high spatial frequencies as described in Section II, Part 4. Comments (two or three sentences) on the frequency-domain filtering in Section II. 2. A table giving the number of edge points as a function of threshold for the image edges.gray (Section III, Part 2). 3. A table giving the number of edge points as a function of threshold for the image edge_noise.gray in Section III, Part 3. 4. A printout of the edge-detected image (use threshold you believe is best) obtained from edge_noise.gray . 5. Your conclusion of the best values for thresh for the images edges.gray , edge_noise.gray , and F15.gray in Section III, Parts 2, 3, and 4. 6. Computer code for your edge detection program. 7. Comments on the performance of the median filters of length 5 and 3 as a function of percentage of pixels corrupted by noise. I Histogram Equalization Use histogram equalization to process the image primate.gray . Obtain a graph (or a printout) of the histogram before and after equalization. You may use the histogram() function. Note: The image primate.gray is 512 by 512 with a 256 byte header, so using the convert program, you should type the following: convert size 512x512+256 primate.gray primate.bmp 2 II Frequency-domain Filtering 1. Call the function Zonal_LP() , which implements a low-pass zonal filter. Let , .....
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This note was uploaded on 04/18/2011 for the course EE 211A taught by Professor Villasenor during the Fall '10 term at UCLA.
- Fall '10