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Keypoint-Based Local Descriptors for Target Recognition in SAR Images: A Comparative Analysis
- Source :
- IEEE geoscience and remote sensing magazine, IEEE geoscience and remote sensing magazine, IEEE, 2021, 9 (1), pp.139-166. ⟨10.1109/MGRS.2020.3005597⟩
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- International audience; Though widely studied over the years, radar target recognition is still far from being solved. Most earlier works rely on holistic features or raw intensity values, which are sensitive to the real-world sources of variability such as changes of pose, configuration, and imaging parameters; articulation; and occlusion. To solve these problems, this article resorts to the local descriptors around keypoints.
- Subjects :
- Synthetic aperture radar
comparative analysis
General Computer Science
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
0211 other engineering and technologies
pose configuration
02 engineering and technology
law.invention
radar target recognition
raw intensity values
law
Radar imaging
holistic features
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Electrical and Electronic Engineering
Radar
Instrumentation
021101 geological & geomatics engineering
business.industry
imaging parameters
SAR images
keypoint-based local descriptors
General Earth and Planetary Sciences
Clutter
020201 artificial intelligence & image processing
Artificial intelligence
business
Articulation (phonetics)
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Subjects
Details
- ISSN :
- 23737468, 24732397, and 21686831
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Geoscience and Remote Sensing Magazine
- Accession number :
- edsair.doi.dedup.....5a44dc0f763b23c89057b2e49988dca7