Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/174902
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dc.contributor.authorJongyoo Kimen_US
dc.contributor.authorTaewan Kimen_US
dc.contributor.authorSanghoon Leeen_US
dc.contributor.authorAlan Conrad Boviken_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:30:00Z-
dc.date.available2020-04-06T07:30:00Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TIP.2017.2717180en_US
dc.identifier.urihttp://localhost/handle/Hannan/174902-
dc.description.abstractCrosstalk is one of the most severe factors affecting the perceived quality of stereoscopic 3D images. It arises from a leakage of light intensity between multiple views, as in auto-stereoscopic displays. Well-known determinants of crosstalk include the co-location contrast and disparity of the left and right images, which have been dealt with in prior studies. However, when a natural stereo image that contains complex naturalistic spatial characteristics is viewed on an auto-stereoscopic display, other factors may also play an important role in the perception of crosstalk. Here, we describe a new way of predicting the perceived severity of crosstalk, which we call the Binocular Perceptual Crosstalk Predictor (BPCP). BPCP uses measurements of three complementary 3D image properties (texture, structural duplication, and binocular summation) in combination with two well-known factors (co-location contrast and disparity) to make predictions of crosstalk on two-view auto-stereoscopic displays. The new BPCP model includes two masking algorithms and a binocular pooling method. We explore a new masking phenomenon that we call duplicated structure masking, which arises from structural correlations between the original and distorted objects. We also utilize an advanced binocular summation model to develop a binocular pooling algorithm. Our experimental results indicate that BPCP achieves high correlations against subjective test results, improving upon those delivered by previous crosstalk prediction models.en_US
dc.format.extent4885,en_US
dc.format.extent4899en_US
dc.publisherIEEEen_US
dc.relation.haspart7953549.pdfen_US
dc.titleQuality Assessment of Perceptual Crosstalk on Two-View Auto-Stereoscopic Displaysen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
Appears in Collections:2017

Files in This Item:
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7953549.pdf4.09 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJongyoo Kimen_US
dc.contributor.authorTaewan Kimen_US
dc.contributor.authorSanghoon Leeen_US
dc.contributor.authorAlan Conrad Boviken_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:30:00Z-
dc.date.available2020-04-06T07:30:00Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TIP.2017.2717180en_US
dc.identifier.urihttp://localhost/handle/Hannan/174902-
dc.description.abstractCrosstalk is one of the most severe factors affecting the perceived quality of stereoscopic 3D images. It arises from a leakage of light intensity between multiple views, as in auto-stereoscopic displays. Well-known determinants of crosstalk include the co-location contrast and disparity of the left and right images, which have been dealt with in prior studies. However, when a natural stereo image that contains complex naturalistic spatial characteristics is viewed on an auto-stereoscopic display, other factors may also play an important role in the perception of crosstalk. Here, we describe a new way of predicting the perceived severity of crosstalk, which we call the Binocular Perceptual Crosstalk Predictor (BPCP). BPCP uses measurements of three complementary 3D image properties (texture, structural duplication, and binocular summation) in combination with two well-known factors (co-location contrast and disparity) to make predictions of crosstalk on two-view auto-stereoscopic displays. The new BPCP model includes two masking algorithms and a binocular pooling method. We explore a new masking phenomenon that we call duplicated structure masking, which arises from structural correlations between the original and distorted objects. We also utilize an advanced binocular summation model to develop a binocular pooling algorithm. Our experimental results indicate that BPCP achieves high correlations against subjective test results, improving upon those delivered by previous crosstalk prediction models.en_US
dc.format.extent4885,en_US
dc.format.extent4899en_US
dc.publisherIEEEen_US
dc.relation.haspart7953549.pdfen_US
dc.titleQuality Assessment of Perceptual Crosstalk on Two-View Auto-Stereoscopic Displaysen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7953549.pdf4.09 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJongyoo Kimen_US
dc.contributor.authorTaewan Kimen_US
dc.contributor.authorSanghoon Leeen_US
dc.contributor.authorAlan Conrad Boviken_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:30:00Z-
dc.date.available2020-04-06T07:30:00Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TIP.2017.2717180en_US
dc.identifier.urihttp://localhost/handle/Hannan/174902-
dc.description.abstractCrosstalk is one of the most severe factors affecting the perceived quality of stereoscopic 3D images. It arises from a leakage of light intensity between multiple views, as in auto-stereoscopic displays. Well-known determinants of crosstalk include the co-location contrast and disparity of the left and right images, which have been dealt with in prior studies. However, when a natural stereo image that contains complex naturalistic spatial characteristics is viewed on an auto-stereoscopic display, other factors may also play an important role in the perception of crosstalk. Here, we describe a new way of predicting the perceived severity of crosstalk, which we call the Binocular Perceptual Crosstalk Predictor (BPCP). BPCP uses measurements of three complementary 3D image properties (texture, structural duplication, and binocular summation) in combination with two well-known factors (co-location contrast and disparity) to make predictions of crosstalk on two-view auto-stereoscopic displays. The new BPCP model includes two masking algorithms and a binocular pooling method. We explore a new masking phenomenon that we call duplicated structure masking, which arises from structural correlations between the original and distorted objects. We also utilize an advanced binocular summation model to develop a binocular pooling algorithm. Our experimental results indicate that BPCP achieves high correlations against subjective test results, improving upon those delivered by previous crosstalk prediction models.en_US
dc.format.extent4885,en_US
dc.format.extent4899en_US
dc.publisherIEEEen_US
dc.relation.haspart7953549.pdfen_US
dc.titleQuality Assessment of Perceptual Crosstalk on Two-View Auto-Stereoscopic Displaysen_US
dc.typeArticleen_US
dc.journal.volume26en_US
dc.journal.issue10en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7953549.pdf4.09 MBAdobe PDF