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dc.contributor.authorPalm, Hans Christianen_GB
dc.date.accessioned2018-11-07T10:08:14Z
dc.date.accessioned2018-11-08T10:09:43Z
dc.date.available2018-11-07T10:08:14Z
dc.date.available2018-11-08T10:09:43Z
dc.date.issued2018
dc.identifier.citationPalm HC. Fast and robust image processing algorithms based on approximations to order statistics. Proceedings of SPIE, the International Society for Optical Engineering. 2018;10648en_GB
dc.identifier.urihttp://hdl.handle.net/123456789/72306
dc.identifier.urihttp://hdl.handle.net/20.500.12242/2024
dc.descriptionPalm, Hans Christian. Fast and robust image processing algorithms based on approximations to order statistics. Proceedings of SPIE, the International Society for Optical Engineering 2018 ;Volum 10648en_GB
dc.description.abstractA test system with four cameras in the infrared and visual spectra is under development at FFI (The Norwegian Defence Research Establishment). The system can be mounted on a high speed jet aircraft, but may also be used in a land-based version. It can be used for image acquisition as well as for development and test of automatic target recognition (ATR) algorithms. The sensors on board generate large amounts of data, and the scene may be rather cluttered or include anomalies (e.g. sun glare). This means we need image processing and pattern recognition algorithms which are robust, fast (real-time), and able to handle complex scenes. Algorithms based on order statistics are known to be robust and reliable. However, they are in general computationally heavy, and thus often unsuitable for real time applications. But approximations to order statistics do exist. Median of medians is one example. This is a technique where an approximation of the median of a sequence is found by first dividing the sequence in subsequences, and then calculating median (of medians) recursively. The algorithm is very efficient, the processing time is of order O(n). By utilizing such techniques for estimating image statistics, the computational challenge can be overcome. In this paper we present strategies for how approximations to order statistics can be applied for developing robust and fast algorithms for image processing, especially visualization and segmentation.en_GB
dc.language.isoenen_GB
dc.subjectTermSet Emneord::Optikk
dc.subjectTermSet Emneord::Bildebehandling
dc.subjectTermSet Emneord::Infrarødkamera
dc.titleFast and robust image processing algorithms based on approximations to order statisticsen_GB
dc.title.alternativeFast and robust image processing algorithms based on approximations to order statisticsen_GB
dc.typeArticleen_GB
dc.date.updated2018-11-07T10:08:14Z
dc.identifier.cristinID1627450
dc.identifier.cristinID1627450
dc.identifier.doi10.1117/12.2304336
dc.source.issn0277-786X
dc.source.issn1996-756X
dc.type.documentJournal article
dc.relation.journalProceedings of SPIE, the International Society for Optical Engineering


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