Astronomical Object Detection With A Robust Hit-Or-Miss Transform Article Swipe
Benjamin Perret
,
Sébastien Lefèvre
,
Christophe Collet
,
B. Vollmer
·
YOU?
·
· 2015
· Open Access
·
YOU?
·
· 2015
· Open Access
·
web: cds.u-strasbg.fr Astronomical object detection is a particularly difficult but very challenging task. Indeed, astronomical images may contain a high noise level due to huge distance within the Universe or to the low photon flow collected on telescope mirrors [1]. Some astronomical objects of interest such as Low Surface Brightness (LSB) galaxies are characterized by a very low signal-to-noise ratio and thus are rather extracted manually and then are sometimes lost or not detected. In this paper, we propose an automatic approach using Mathemati-cal Morphology, well-known for its appropriate care of spa-tial information (shape and luminance profile of LSB galax-ies is known). In order to be able to detect objects in noisy environments, we propose a new morphological operator for template matching, namely a robust hit-or-miss transform. 1.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.483.5302
- OA Status
- green
- Cited By
- 5
- References
- 10
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1569391344
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Raw OpenAlex JSON
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https://openalex.org/W1569391344Canonical identifier for this work in OpenAlex
- Title
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Astronomical Object Detection With A Robust Hit-Or-Miss TransformWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2015Year of publication
- Publication date
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2015-01-20Full publication date if available
- Authors
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Benjamin Perret, Sébastien Lefèvre, Christophe Collet, B. VollmerList of authors in order
- Landing page
-
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.483.5302Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
-
https://hal.science/hal-00516054Direct OA link when available
- Concepts
-
Computer science, Luminance, Computer vision, Artificial intelligence, Brightness, Galaxy, Noise (video), Telescope, Object (grammar), Surface brightness, Object detection, Least significant bit, Physics, Image (mathematics), Pattern recognition (psychology), Astronomy, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
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2015: 1, 2013: 2Per-year citation counts (last 5 years)
- References (count)
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10Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.is_published | False |
| primary_location.raw_source_name | https://dpt-info.u-strasbg.fr/~lefevre/publis/eusipco2008.pdf |
| primary_location.landing_page_url | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.483.5302 |
| publication_date | 2015-01-20 |
| publication_year | 2015 |
| referenced_works | https://openalex.org/W105733129, https://openalex.org/W2017936102, https://openalex.org/W1561442812, https://openalex.org/W2124453429, https://openalex.org/W2150281266, https://openalex.org/W2109853861, https://openalex.org/W2161350600, https://openalex.org/W1986537099, https://openalex.org/W3099108928, https://openalex.org/W2142238829 |
| referenced_works_count | 10 |
| abstract_inverted_index.a | 6, 18, 55, 115, 123 |
| abstract_inverted_index.1. | 127 |
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| abstract_inverted_index.an | 79 |
| abstract_inverted_index.as | 46 |
| abstract_inverted_index.be | 105 |
| abstract_inverted_index.by | 54 |
| abstract_inverted_index.in | 110 |
| abstract_inverted_index.is | 5, 100 |
| abstract_inverted_index.of | 43, 90, 97 |
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| abstract_inverted_index.or | 29, 71 |
| abstract_inverted_index.to | 23, 30, 104, 107 |
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| abstract_inverted_index.and | 60, 66, 94 |
| abstract_inverted_index.are | 52, 62, 68 |
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| abstract_inverted_index.due | 22 |
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| abstract_inverted_index.this | 75 |
| abstract_inverted_index.thus | 61 |
| abstract_inverted_index.very | 10, 56 |
| abstract_inverted_index.web: | 0 |
| abstract_inverted_index.(LSB) | 50 |
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| abstract_inverted_index.noise | 20 |
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| abstract_inverted_index.order | 103 |
| abstract_inverted_index.ratio | 59 |
| abstract_inverted_index.task. | 12 |
| abstract_inverted_index.using | 82 |
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| abstract_inverted_index.detect | 108 |
| abstract_inverted_index.images | 15 |
| abstract_inverted_index.namely | 122 |
| abstract_inverted_index.object | 3 |
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| abstract_inverted_index.rather | 63 |
| abstract_inverted_index.robust | 124 |
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| abstract_inverted_index.Indeed, | 13 |
| abstract_inverted_index.Surface | 48 |
| abstract_inverted_index.contain | 17 |
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| abstract_inverted_index.objects | 42, 109 |
| abstract_inverted_index.profile | 96 |
| abstract_inverted_index.propose | 78, 114 |
| abstract_inverted_index.Universe | 28 |
| abstract_inverted_index.approach | 81 |
| abstract_inverted_index.distance | 25 |
| abstract_inverted_index.galaxies | 51 |
| abstract_inverted_index.interest | 44 |
| abstract_inverted_index.manually | 65 |
| abstract_inverted_index.operator | 118 |
| abstract_inverted_index.spa-tial | 91 |
| abstract_inverted_index.template | 120 |
| abstract_inverted_index.automatic | 80 |
| abstract_inverted_index.collected | 35 |
| abstract_inverted_index.detected. | 73 |
| abstract_inverted_index.detection | 4 |
| abstract_inverted_index.difficult | 8 |
| abstract_inverted_index.extracted | 64 |
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| abstract_inverted_index.luminance | 95 |
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| abstract_inverted_index.particularly | 7 |
| abstract_inverted_index.Mathemati-cal | 83 |
| abstract_inverted_index.characterized | 53 |
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| abstract_inverted_index.morphological | 117 |
| abstract_inverted_index.signal-to-noise | 58 |
| abstract_inverted_index.cds.u-strasbg.fr | 1 |
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| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.5763094 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |