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Using image quality measures and features to choose good images for classification of ISAR imagery
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| dc.contributor.author |
Steyn, JM
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| dc.contributor.author |
Nel, Willem AJ
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| dc.date.accessioned | 2016-08-19T08:09:21Z | |
| dc.date.available | 2016-08-19T08:09:21Z | |
| dc.date.issued | 2014-10 | |
| dc.identifier.citation | Steyn, JM and Nel WAJ. 2014. Using image quality measures and features to choose good images for classification of ISAR imagery. In: International Radar Conference 2014: Catching the Invisible, 13-17 October 2014. Lille, France, 6pp. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10204/8699 | |
| dc.description | Copyright: 2014 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. | en_US |
| dc.description.abstract | Most research efforts in ISAR focus on techniques to form the image via autofocus or on classification (assuming that the ISAR imagery is already generated). An important step between image formation and classification is to determine which of the ISAR images generated by the sensor really provides the most useful information for classification. This paper proposes multiple quality measures (QM) to automatically select ISAR images that carry good classification information. These features are used to also investigate the effect of dwell-time on ISAR imagery. Measured data of maritime vessels are used to evaluate the quality measures and to determine the minimum dwell-time for ISAR image formation. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.ispartofseries | Worklist;14187 | |
| dc.subject | Inverse synthetic aperture radar | en_US |
| dc.subject | ISAR | en_US |
| dc.subject | Dwelltime | en_US |
| dc.subject | Quality measure | en_US |
| dc.subject | Image contrast | en_US |
| dc.subject | Image entropy | en_US |
| dc.subject | Signal-to-noise ratio | en_US |
| dc.subject | SNR | en_US |
| dc.subject | Maritime vessels | en_US |
| dc.title | Using image quality measures and features to choose good images for classification of ISAR imagery | en_US |
| dc.type | Conference Presentation | en_US |
| dc.identifier.apacitation | Steyn, J., & Nel, W. (2014). Using image quality measures and features to choose good images for classification of ISAR imagery. IEEE. http://hdl.handle.net/10204/8699 | en_ZA |
| dc.identifier.chicagocitation | Steyn, JM, and WAJ Nel. "Using image quality measures and features to choose good images for classification of ISAR imagery." (2014): http://hdl.handle.net/10204/8699 | en_ZA |
| dc.identifier.vancouvercitation | Steyn J, Nel W, Using image quality measures and features to choose good images for classification of ISAR imagery; IEEE; 2014. http://hdl.handle.net/10204/8699 . | en_ZA |
| dc.identifier.ris | TY - Conference Presentation AU - Steyn, JM AU - Nel, WAJ AB - Most research efforts in ISAR focus on techniques to form the image via autofocus or on classification (assuming that the ISAR imagery is already generated). An important step between image formation and classification is to determine which of the ISAR images generated by the sensor really provides the most useful information for classification. This paper proposes multiple quality measures (QM) to automatically select ISAR images that carry good classification information. These features are used to also investigate the effect of dwell-time on ISAR imagery. Measured data of maritime vessels are used to evaluate the quality measures and to determine the minimum dwell-time for ISAR image formation. DA - 2014-10 DB - ResearchSpace DP - CSIR KW - Inverse synthetic aperture radar KW - ISAR KW - Dwelltime KW - Quality measure KW - Image contrast KW - Image entropy KW - Signal-to-noise ratio KW - SNR KW - Maritime vessels LK - https://researchspace.csir.co.za PY - 2014 T1 - Using image quality measures and features to choose good images for classification of ISAR imagery TI - Using image quality measures and features to choose good images for classification of ISAR imagery UR - http://hdl.handle.net/10204/8699 ER - | en_ZA |
