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dc.contributor.authorConni, Michele
dc.contributor.authorDeborah, Hilda
dc.contributor.authorNussbaum, Peter
dc.contributor.authorGreen, Philip John
dc.date.accessioned2021-10-28T08:26:07Z
dc.date.available2021-10-28T08:26:07Z
dc.date.created2021-08-12T12:51:05Z
dc.date.issued2021
dc.identifier.issn1017-9909
dc.identifier.urihttps://hdl.handle.net/11250/2826186
dc.description.abstractThe stationarity of a texture can be considered a fundamental property of images, although the property of stationarity is difficult to define precisely. We propose a stationarity test based on multiscale, locally stationary, 2D wavelets. Three separate experiments were performed to evaluate the capabilities and the limitations of this test. The experiments comprised a chessboard stationarity analysis, two classification tasks, and a psychophysical experiment. The classification tasks were performed on 110 texture images from a texture database. In one subtask, five texture feature vectors were extracted from each image and the classification accuracy of two classical methods compared, whereas in the second subtask, the classification accuracy of several methods was compared to the descriptors defined for each image within the database. In the psychophysical experiment, the correlation between the classification results and observer judgements of texture similarity were determined. It was found that a combination of wavelet shrinkage and rotation-invariant local binary pattern best predicted the observer response. The results show that the proposed stationarity test is able to provide relevant information for texture analysis.en_US
dc.language.isoengen_US
dc.publisherSociety of Photo-optical Instrumentation Engineersen_US
dc.titleVisual and data stationarity of texture imagesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_US
dc.source.journalJournal of Electronic Imaging (JEI)en_US
dc.identifier.doi10.1117/1.JEI.30.4.043001
dc.identifier.cristin1925569
dc.relation.projectNorges forskningsråd: 274881en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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