SUBJECTIVE SIMILARITY EVALUATION FOR SCENIC BILEVEL IMAGES
dc.contributor.author | Zhai, Yuanhao | |
dc.contributor.author | Neuhoff, David | |
dc.contributor.author | Pappas, Thrasyvoulos | |
dc.date.accessioned | 2015-05-01T02:19:22Z | |
dc.date.available | 2015-05-01T02:19:22Z | |
dc.date.issued | 2014-05-09 | |
dc.identifier.citation | IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), pp. 156-160, May 2014 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/111057 | |
dc.description.abstract | In order to provide ground truth for subjectively comparing compression methods for scenic bilevel images, as well as for judging objective similarity metrics, this paper describes the subjective similarity rating of a collection of distorted scenic bilevel images. Unlike text, line drawings, and silhouettes, scenic bilevel images contain natural scenes, e.g., landscapes and portraits. Seven scenic images were each distorted in forty-four ways, including random bit flipping, dilation, erosion and lossy compression. To produce subjective similarity ratings, the distorted images were each viewed by 77 subjects. These are then used to compare the performance of four compression algorithms and to assess how well percentage error and SmSIM work as bilevel image similarity metrics. These subjective ratings can also provide ground truth for future tests of objective bilevel image similarity metrics. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) | en_US |
dc.subject | bilevel image similarity | en_US |
dc.subject | image quality | en_US |
dc.subject | subjective evaluation | en_US |
dc.title | SUBJECTIVE SIMILARITY EVALUATION FOR SCENIC BILEVEL IMAGES | en_US |
dc.type | Working Paper | en_US |
dc.subject.hlbsecondlevel | Electrical Engineering | |
dc.subject.hlbsecondlevel | Computer Science | |
dc.subject.hlbtoplevel | Engineering | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Electrical Engineering and Computer Science, Department of | en_US |
dc.contributor.affiliationother | EECS Department, Northwestern University | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/111057/4/SUBJECTIVE SIMILARITY EVALUATION FOR SCENIC BILEVEL IMAGES.pdf | |
dc.identifier.source | 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) | en_US |
dc.owningcollname | Electrical Engineering and Computer Science, Department of (EECS) |
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