Title :
Recognizing chromospheric objects via Markov chain Monte Carlo
Author :
Turmon, Michael J. ; Mukhtar, Saleem
Author_Institution :
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Abstract :
The solar chromosphere consists of three classes which contribute differentially to ultraviolet radiation reaching the Earth. We describe a data set of solar images, means of segmenting the images into the constituent classes, and a novel high-level representation for compact objects based on a triangulated spatial `membership function.´ Such representations are fitted in a variable-dimension Markov chain Monte Carlo scheme
Keywords :
Markov processes; Monte Carlo methods; astronomical techniques; astronomy computing; chromosphere; image representation; image segmentation; object recognition; solar radiation; ultraviolet astronomy; Earth; Markov chain; Monte Carlo method; chromospheric objects recognition; compact objects; high-level representation; image segmentation; solar chromosphere; solar images; triangulated spatial membership function; ultraviolet radiation; variable-dimension scheme; Atmospheric modeling; Bayesian methods; Earth; Fuses; Image segmentation; Labeling; Laboratories; Monte Carlo methods; Pixel; Propulsion;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632105
