CS-467 Image processing and Computer Vision
The purpose of this project is to test the efficiency of unsharp masking and edge detection
for details enhancement
Use VEGA program
1. Choose an image ( , )f x y and choose some detail you want to enhance. Try to enhance it using
Global frequency correction mean and median filters with a window size equal and larger than sizes of
your detail of interest. Save the best resulting image that you obtained. Your quality criterion is your
1. Choose an image ( , )f x y
2. Detect edges using Sobel, Prewitt, Laplace-1, Laplace-2, edge detectors. Use Edge Detection
Edge Detection menu item in VEGA. Save your results.
3. Detect upward, downward, and "global" edges on the same image using Stack Filtering Edge
Detector. Use Edge Detection Precise Edge Detection with "Stack Filtration" box checked in
VEGA. Detect also upward, downward, and "global" edges on the same image using Precise Edge
Detector. Use Edge Detection Precise Edge Detection with "Stack Filtration" and "Segmentation"
boxes unchecked in VEGA. Save your results.
4. Adding an edged image to the original one (using appropriate coefficients-weights), try to enhance
image details. Save your results. Compare the resulting images to each other. Which details are better
enhanced using which detector?
5. Prepare a technical report with the references to your saved results.
Bonus (100 % extra credit score). Design a Matlab function for edge detection using Sobel, Prewit,
and TBF (Stack) operators (not employing edge detection functions from Matlab), which accepts an
image and the type of detector as parameters (3 options should be reserved for the TBF (Stack)
detector) and return a resulting image.
6. Put your resulting images and the report in the subfolder Project 6 (you need to create it) located in
the designated folder (named by your last name) in the folder
sfs01classesCS 467 001Class Data (The folder sfs01classes is mapped from all the lab computers,
so you can easily find it through File Explorer (Computer) in Windows 7. A shortcut to the Classes
folder is also available on the desktop of the lab computers.