Histogram modelling-based no reference blur quality measure

作者：

Highlights：

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• A normalized, simple, fast, and faithful objective blind blur quality measure is proposed.

• The Human Visual System (HVS) is sensitive to blur effect especially on high frequency components corresponding to edges and texture.

• The histogram of the absolute quantified DCT coefficients of the edge map can be modelled by using an exponential Probability Density Function (PDF).

• The statistical parameter of the exponential PDF is used as a cue to characterize the blur effect.

摘要

•A normalized, simple, fast, and faithful objective blind blur quality measure is proposed.•The Human Visual System (HVS) is sensitive to blur effect especially on high frequency components corresponding to edges and texture.•The histogram of the absolute quantified DCT coefficients of the edge map can be modelled by using an exponential Probability Density Function (PDF).•The statistical parameter of the exponential PDF is used as a cue to characterize the blur effect.

论文关键词：Blind image quality,Blur,High frequencies analysis,Histogram,probability density function

论文评审过程：Received 21 December 2016, Revised 30 August 2017, Accepted 31 August 2017, Available online 12 September 2017, Version of Record 18 September 2017.

论文官网地址：https://doi.org/10.1016/j.image.2017.08.014