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dc.contributor.authorKolås, Øyvind
dc.contributor.authorFarup, Ivar
dc.contributor.authorRizzi, Alessandro
dc.date.accessioned2011-10-17T06:27:18Z
dc.date.available2011-10-17T06:27:18Z
dc.date.issued2011
dc.identifier.citationKolås, Ø., Farup, I. & Rizzi, A. (2011). Spatio-Temporal Retinex-Inspired Envelope with Stochastic Sampling: A Framework for Spatial Color Algorithms. Journal of Imaging Science and Technology, 55 (4)en_US
dc.identifier.urihttp://hdl.handle.net/11250/142542
dc.descriptionThis is the copy of journal's version originally published in Journal of Imaging Science and Technology. Reprinted with permission of IS & T: The Society for Imaging Science and Technology sole copyright owners of the Journal of Imaging Science and Technology: www.imaging.orgen_US
dc.description.abstractThe authors present a new framework for algorithms for a wide range of image enhancement and reproduction applications, named STRESS Spatio-Temporal Retinex-inspired Envelope with Stochastic Sampling. The algorithms work by recalculating each pixel using envelopes for local upper and lower bounds in the image. The envelopes are obtained sampling neighbor pixels and can be interpreted as local reference maximum and minimum. This approach derives from a computational simplification of previous spatial color algorithms like Retinex or ACE. With the proposed method, various tasks such as local contrast stretching, automatic color correction, high dynamic range image rendering, spatial color gamut mapping, and color to grayscale conversion can be performed with good results. The algorithm exhibits behaviors in line with some aspects of the human visual system, e.g., simultaneous contrast.en_US
dc.language.isoengen_US
dc.publisherThe Society for Imaging Science and Technologyen_US
dc.titleSpatio-Temporal Retinex-Inspired Envelope with Stochastic Sampling: A Framework for Spatial Color Algorithmsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.subject.nsiVDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429en_US
dc.source.pagenumber10 s.en_US
dc.source.volume55en_US
dc.source.journalJournal of Imaging Science and Technologyen_US
dc.source.issue4en_US
dc.identifier.doi10.2352/J.ImagingSci.Technol.2011.55.4.040503en_US


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