Sheena Patel Keith Hawkins Joey Starnes Daniel Jacobs

1. Image Processing Comet Finding Group: Supernova Sheena Patel Keith Hawkins Joey Starnes Daniel Jacobs

2. Introduction • The goal of this project is to create a suite of programs using MATLAB to find possible comets from images taken by the SOHO satellite. • MATLAB- a program that has integrated image processing toolboxes. • Image Processing

3. The SOHO Satellite • SOHO stands for the Solar and Heliospheric Observatory. • SOHO is an international collaboration between ESA and NASA • SOHO studies the Sun from its deep core to the solar winds • SOHO orbits in a special orbit called L1 Lagrangian point, which allows it to observe the sun 24/7 • We used data from the Large Angle and Spectrometric Coronagraph (LASCO) to run through our programs. Figure 1: Example input picture Courtesy of: http://sohowww.nascom.nasa.gov/data/realtime/c2/1024/latest.html

4. General Introduction to Comets a. b. • Comets are small, irregularly shaped astronomical bodies • Most Comets are composed of a mixture of small grains and frozen gases. • Comets have highly eccentric orbits which make them extremely bright and visible to the naked eye • Therefore comets have a unique structure built of two parts: • Nucleus • Tail Figure 2: (a) example of a circle and ellipse. (B) Structure of a comet Courtesy of: http://www.solarviews.com/eng/comet.htm

5. Concepts Behind the Project • Images coming from LASCO, once masked, have bright dots that can either be stars or comets • In order to extract the comets from the background stars the project makes use running images in sets of four and the program will watch the dots to see which dots are not moving in harmony with the background dots or stars Figure 3: picture of SOHO comet Courtesy of: http://www.cnn.com/2005/TECH/space/01/26/comet.contest/

6. Procedure: Step 1 • Get pictures from directory • Isolate date and time from picture name • Calculate time between images • Store date, time, and elapsed time for later use *See Animations

7. Procedure: Step 2 • involves using MATLAB to determine the coordinates of all of the bright spots on the masked images. • writing code to seek out all the bright spots Figure 4: Masked SOHO image *See Animations

8. Procedure: Step 3 • takes the output of step 2 • takes multiple masked images and calculates distances • applies distance constraints to make a list of possible trajectories *See Animations

9. Procedure: Step 4 • Take input of points in 2 images • Connect into paths through 4 images • Check for consistent distance • Check for angles and linear relationship *See Animations

10. Procedure: Step 5 • Take in coordinates of comet paths • Make circle around coordinates • Change contrast inside circle • Results in highlighted comet *See Animations

11. Procedure: Step 6 • Main Loop • Connects previous five steps • Coordinates inputs and outputs • Prints final comet images *See Animations

12. Applications • Program used to find comets • Increased knowledge of galactic neighborhood • NASA can keep tabs on objects close to earth 3. Programs can be modified for other purposes .

13. Conclusions • Although there was not enough time to go through new data, the programs that was written by team supernova was able to identify previously known comets from SOHO data!! Figure : Picture of a SOHO comet Courtesy of: http://www.esa.int/esaCP/ESA26YTM5JC_FeatureWeek_1.html

14. Movie Animation

15. 1 Comets from May 6, 2005 2 3 4

16. ??????ANY QUESTIONS??????