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Reduced reference image quality assessment based on Weibull statistics

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2 Author(s)
Wufeng Xue ; Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, China ; Xuanqin Mou

Theories in fragmentation have proved that the statistics of image gradient magnitude followed a Weibull distribution, with β (scale) and γ (shape) as free parameters, which are demonstrated to be strongly correlated with brain response. In this paper, we chose β extracted from the proposed strongest component map (SCM) in scale space, as the reduced reference (RR) feature, and developed a novel method for reduced reference image quality assessment (RRIQA) named βW-SCM. For each scale, the SCM was constructed by assembling coefficients with maximum amplitude among different orientations into a single map. The Weibull parameters were then estimated from the SCM. The final image quality was computed by summing the geometric mean of the defined absolute and relative deviations of β. Performance evaluation on the well-known LIVE database demonstrated an outstanding advantage of low RR feature data rate with nearly the same prediction accuracy and consistency.

Published in:

Quality of Multimedia Experience (QoMEX), 2010 Second International Workshop on

Date of Conference:

21-23 June 2010