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

Volume

3

fYear

1997

Firstpage

320

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.632105

Filename

632105