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dc.contributor.authorSimone, Gabriele
dc.contributor.authorPedersen, Marius
dc.contributor.authorHardeberg, Jon Yngve
dc.contributor.authorRizzi, Alessandro
dc.date.accessioned2011-05-04T09:06:42Z
dc.date.available2011-05-04T09:06:42Z
dc.date.issued2009
dc.identifier.citationSimone, G., Pedersen, M., Hardeberg, J. Y., & Rizzi, A. (2009). Measuring perceptual contrast in a multilevel framework. In B. E. Rogowitz & T. N. Pappas (Eds.), Human vision and electronic imaging XIV 19-22 January 2009, San Jose, California, United States (pp. 9). Bellingham, Wash.: SPIE.en_US
dc.identifier.isbn9780819474902
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/11250/142502
dc.descriptionThis is the copy of journal's version originally published in Proc. SPIE 7240. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7en_US
dc.description.abstractIn this paper, we propose and discuss some approaches for measuring perceptual contrast in digital images. We start from previous algorithms by implementing different local measures of contrast and a parameterized way to recombine local contrast maps and color channels. We propose the idea of recombining the local contrast maps and the channels using particular measures taken from the image itself as weighting parameters. Exhaustive tests and results are presented and discussed, in particular we compare the performance of each algorithm in relation to perceived contrast by observers. Current results show an improvement in correlation between contrast measures and observers perceived contrast when the variance of the three color channels separately is used as weighting parameter for local contrast mapsen_US
dc.language.isoengen_US
dc.publisherSociety of Photo Optical Instrumentation Engineers (SPIE)en_US
dc.relation.ispartofseriesProceedings of SPIE;7240
dc.titleMeasuring perceptual contrast in a multilevel frameworken_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.pagenumber9 s.en_US
dc.identifier.doihttp://dx.doi.org/10.1117/12.805477


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