No-reference image quality assessment based on spatial and spectral entropies

作者：

Highlights：

• SSEQ extracts a 12-dimensional local entropy feature vector from the inputs.

• SSEQ correlates highly with the human subjective impressions of image quality.

• SSEQ has a relatively low time complexity.

摘要

•SSEQ extracts a 12-dimensional local entropy feature vector from the inputs.•SSEQ correlates highly with the human subjective impressions of image quality.•SSEQ has a relatively low time complexity.

论文关键词：Image quality assessment,No-reference,Spatial entropy,Spectral entropy,Support vector machine

论文评审过程：Received 4 October 2013, Revised 13 June 2014, Accepted 15 June 2014, Available online 23 June 2014.

论文官网地址：https://doi.org/10.1016/j.image.2014.06.006