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dc.contributor.author Sazzad, Z. M. Parvez
dc.contributor.author Akhter, Roushain
dc.contributor.author Baltes, J.
dc.contributor.author Horita, Y.
dc.date.accessioned 2015-05-14T16:38:36Z
dc.date.available 2015-05-14T16:38:36Z
dc.date.issued 2012-7-19
dc.identifier.citation Z. M. Parvez Sazzad, Roushain Akhter, J. Baltes, and Y. Horita, “Objective No-Reference Stereoscopic Image Quality Prediction Based on 2D Image Features and Relative Disparity,” Advances in Multimedia, vol. 2012, Article ID 256130, 16 pages, 2012. doi:10.1155/2012/256130
dc.identifier.uri http://dx.doi.org/10.1155/2012/256130
dc.identifier.uri http://hdl.handle.net/1993/30504
dc.description.abstract Stereoscopic images are widely used to enhance the viewing experience of three-dimensional (3D) imaging and communication system. In this paper, we propose an image feature and disparity dependent quality evaluation metric, which incorporates human visible system characteristics. We believe perceived distortions and disparity of any stereoscopic image are strongly dependent on local features, such as edge (i.e., nonplane areas of an image) and nonedge (i.e., plane areas of an image) areas within the image. Therefore, a no-reference perceptual quality assessment method is developed for JPEG coded stereoscopic images based on segmented local features of distortions and disparity. Local feature information such as edge and non-edge area based relative disparity estimation, as well as the blockiness and the edge distortion within the block of images are evaluated in this method. Subjective stereo image database is used for evaluation of the metric. The subjective experiment results indicate that our metric has sufficient prediction performance.
dc.title Objective No-Reference Stereoscopic Image Quality Prediction Based on 2D Image Features and Relative Disparity
dc.type Journal Article
dc.language.rfc3066 en
dc.description.version Peer Reviewed
dc.rights.holder Copyright © 2012 Z. M. Parvez Sazzad et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.date.updated 2015-03-29T13:33:42Z


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