Full-Reference Image Quality Assessment Approach Based on Image Separation

DOI

10.2991/icaemt-15.2015.101How to use a DOI?

Keywords

Image Quality Assessment; Blind Source Seperation.

Abstract

In this paper, a full-reference image quality assessment (IQA) approach based on blind source separation algorithm is present. After the reference image is divided into several patches, the scatter plot of these patches is contained within a simplicial cone. The mixing matrix is estimated by the parameter of the simplicial cone. The sources of the reference image and the distorted image are extracted by mutiplying the image pathces by the mixing matrix. Different sources of the reference image and the distorted image are used to calculate the structural similarity (SSIM) index values. SSIM values of different sources are weighted and summed to calculate the final objective IQA criterion. Experimental results show that the IQA approach outperforms the traditional single source IQA approach.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bin Wang
PY  - 2015/08
DA  - 2015/08
TI  - Full-Reference Image Quality Assessment Approach Based on Image Separation
BT  - Proceedings of the 2015 International Conference on Advanced Engineering Materials and Technology
PB  - Atlantis Press
SP  - 524
EP  - 527
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaemt-15.2015.101
DO  - 10.2991/icaemt-15.2015.101
ID  - Wang2015/08
ER  -