Object Detection With Component-Graphs in Multi-Band Images: Application to Source Detection in Astronomical Images
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...
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| Main Authors: | , , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/92455abf4393453b94404dbebcdbc78c |
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| Summary: | 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. |
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