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CE 261: Lab #4 ImageVision Libraries Satellite Application Development, Part IIMay 25, 1995 1

CE 261: Lab #4

ImageVision Libraries Satellite Application

Development, Part II

Spring 1995

Instructor: Dr. Craig M. Wittenbrink

Office: Applied Science Bldg. #309

Phone: (408) 459 4099

craig@cse.ucsc.edu

Due: Friday June 9. Labs are due at the beginning of class.

Lab Environment: Computer Engineering/Computer and Information Sciences educational lab. Silicon Graphics Indy?s and Indigos.

Location: Applied Sciences 213

Lab Hours: Any time, but you need a keycode

1.0 Description

In Lab #2, and Lab #3 you developed software that performed low level image processing on satellite images. In the fourth and final lab, you are to implement some mid level vision operations. Using any of the operators in the ImageVision libraries to assist you, segment out the clouds within the satellite images of your choice. The segmentation is to separate clouds from the background, ground, and each other. Ideas for segmentation are to use the inherent highpass filters and/or thresholding to find areas of discontinuity, then perform a merging operation to combine like areas (stitch up lines with breaks, etc.), and finally perform connected components on a binary image. Although it is not required, one may like to use the results of the connected components to decide which are clouds (and which type) and are which aren?t by using the area, central moments, or other simple decision parameters.

2.0 Tasks

1. Preprocess, Via Sobel, thresholding, Laplacian, etc. The ImageVision libraries [1] provide a variety of approaches. Please see the graphical examples in the rear of the Image Vision libraries programming guide.

2. Segment, Is it easiest to see areas of discontinuities or areas of similarities? Divide the satellite data into clouds/ocean, coastline in any method you see fit. Work on a scheme to combine segmentations into reasonable objects.

CE 261: Lab #4 ImageVision Libraries Satellite Application Development, Part IIMay 25, 1995 2

3. Connected components, an algorithm for connected components is provided in Gonzalez and Woods, pages 42-43 [2]. A completely specified pseudo code connected component algorithm is provided in Haralick and Shapiro, pages 29-48 [3].

4. Decision vectors (Optional). Once you have done the connected components there are a variety of simple methods to separate them. How many pixels belong in a given component (area), what is the long axis of a component, the short axis, the ratio of long to short axes etc.

5. Illustration of components (Required). Show in the image the separate components, either with number labels overlaid on the original image, pseudo colors with a key, or a similar scheme to illustrate the effectiveness of your algorithm. An executable version of the program is to be placed in your home directory, along with a script which will run the program on the images of your choice. Please chmod a+rx your program and script.

References

[1] ImageVision Library Programming Guide, by Jackie Neider and Eleanor Bassler, Document Number 007-1387-030, Silicon Graphics, 1993.

[2] Gonzalez and Woods, Digital Image Processing. Addison-Wesley, 1992

[3] Haralick and Shapiro, Computer and Robot Vision. Addison-Wesley, 1992.