Quaternionic wavelet coefficients modeling for a Reduced-Reference metric
作者：
Highlights：
• Description of Quaternionic Wavelet Transform (QWT) and Information Criteria (IC).
• Proposition of a probability density function (PDF) for each QWT features.
• Reference image’s PDF and the distributions of degraded image are compared.
• QWT’s shift invariant magnitude provides information to describe the degradation.
• QWT’s structural phase completes structure analysis and is seen as a texture feature.
• Proposed metric gives better prediction (accuracy and monotonicity) than RRIQA.
• RRIQA is the most Reduced-Reference measure used in the image processing literature.
• Proposed metric remains competitive against several classical Full-Reference metrics.
摘要
Highlights•Description of Quaternionic Wavelet Transform (QWT) and Information Criteria (IC).•Proposition of a probability density function (PDF) for each QWT features.•Reference image’s PDF and the distributions of degraded image are compared.•QWT’s shift invariant magnitude provides information to describe the degradation.•QWT’s structural phase completes structure analysis and is seen as a texture feature.•Proposed metric gives better prediction (accuracy and monotonicity) than RRIQA.•RRIQA is the most Reduced-Reference measure used in the image processing literature.•Proposed metric remains competitive against several classical Full-Reference metrics.
论文关键词：Quaternionic Wavelet Transform,Information Criteria,Reduced-Reference Image Quality Assessment,Model selection
论文评审过程：Received 2 September 2014, Revised 20 March 2015, Accepted 9 June 2015, Available online 14 July 2015, Version of Record 23 July 2015.
论文官网地址：https://doi.org/10.1016/j.image.2015.06.003
