Poster abstract details
Low Surface Brightness Segmentation Methods
Abstract
In this study the efficacy of three pieces of segmentation software will be compared to one another with respect to their low surface
brightness (LSB) detection capabilities. Source Extractor NoiseChisel and ProFound will be judged based on object definition,
noise separation, flexibility, ease of use and efficiency. Each tool created a segmentation map from an SDSS Stripe 82 image of the
Abell 267 cluster in the r-deep band, and the identified objects were subtracted. A preliminary analysis suggests that NoiseChisel
may be the most effective tool for LSB segmentation due to its additional segmentation of diffuse LSB components from sky.
brightness (LSB) detection capabilities. Source Extractor NoiseChisel and ProFound will be judged based on object definition,
noise separation, flexibility, ease of use and efficiency. Each tool created a segmentation map from an SDSS Stripe 82 image of the
Abell 267 cluster in the r-deep band, and the identified objects were subtracted. A preliminary analysis suggests that NoiseChisel
may be the most effective tool for LSB segmentation due to its additional segmentation of diffuse LSB components from sky.