Sparse representation-based image quality assessment

作者：

Highlights：

• A sparse representation-based method for image quality assessment is proposed.

• The proposed method is designed to extract and compare perceptually important structures in images.

• Our method achieves competitive performance with the state-of-the-art.

• The proposed method consistently produces (statistically significant) lower error compared to the rival methods.

摘要

Highlights•A sparse representation-based method for image quality assessment is proposed.•The proposed method is designed to extract and compare perceptually important structures in images.•Our method achieves competitive performance with the state-of-the-art.•The proposed method consistently produces (statistically significant) lower error compared to the rival methods.

论文关键词：Dictionary learning,Image quality assessment,Sparse representation,Structural similarity

论文评审过程：Received 12 November 2013, Revised 30 September 2014, Accepted 30 September 2014, Available online 13 October 2014.

论文官网地址：https://doi.org/10.1016/j.image.2014.09.010