Object Detection with Component-Graphs in Multi-Band Images: Application to Source Detection in Astronomical Images

Thanh Xuan Nguyen, Giovanni Chierchia, Oleksandra Razim, Reynier F. Peletier, Laurent Najman*, Hugues Talbot, Benjamin Perret

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
37 Downloads (Pure)

Abstract

In the context of mathematical morphology, component-graphs are complex but powerful structures for multi-band image modeling, processing, and analysis. In this work, we propose a novel multi-band object detection method relying on the component-graphs and statistical hypothesis tests. Our analysis shows that component-graphs are better at capturing image structures compared to the classical component-trees, with significantly higher detection capacity. Besides, we introduce two filtering algorithms to identify duplicated and partial nodes in the component-graphs. The proposed method, applied to the detection of sources on astronomical images, demonstrates a significant improvement in detecting faint objects on both multi-band simulated and real astronomical images compared to the state of the art.

Original languageEnglish
Pages (from-to)156482-156491
Number of pages10
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

Keywords

  • astronomical object
  • component-graphs
  • Morphology
  • object detection

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