Paper
18 January 2010 Scene classification with respect to image quality measurements
Kyung Hoon Oh, Sophie Triantaphillidou, Ralph E. Jacobson
Author Affiliations +
Proceedings Volume 7529, Image Quality and System Performance VII; 752908 (2010) https://doi.org/10.1117/12.838302
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
Psychophysical image quality assessments have shown that subjective quality depended upon the pictorial content of the test images. This study is concerned with the nature of scene dependency, which causes problems in modeling and predicting image quality. This paper focuses on scene classification to resolve this issue and used K-means clustering to classify test scenes. The aim was to classify thirty two original test scenes that were previously used in a psychophysical investigation conducted by the authors, according to their susceptibility to sharpness and noisiness. The objective scene classification involved: 1) investigation of various scene descriptors, derived to describe properties that influence image quality, and 2) investigation of the degree of correlation between scene descriptors and scene susceptibility parameters. Scene descriptors that correlated with scene susceptibility in sharpness and in noisiness are assumed to be useful in the objective scene classification. The work successfully derived three groups of scenes. The findings indicate that there is a potential for tackling the problem of sharpness and noisiness scene susceptibility when modeling image quality. In addition, more extensive investigations of scene descriptors would be required at global and local image levels in order to achieve sufficient accuracy of objective scene classification.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyung Hoon Oh, Sophie Triantaphillidou, and Ralph E. Jacobson "Scene classification with respect to image quality measurements", Proc. SPIE 7529, Image Quality and System Performance VII, 752908 (18 January 2010); https://doi.org/10.1117/12.838302
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image quality

Scene classification

Quality measurement

Edge detection

Image processing

MATLAB

Algorithm development

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