Image quality assessment by preprocessing and full reference model combination
Simone Bianco, Gianluigi Ciocca, Francesco Marini, Raimondo Schettini · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
This paper focuses on full-reference image quality assessment and presents different computational strategies aimed to improve the robustness and accuracy of some well known and widely used state of the art models, namely the Structural Similarity approach (SSIM) by Wang and Bovik and the S-CIELAB spatial-color model by Zhang and Wandell. We investigate the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2. We show that the proposed quality assessment metric better correlates with the experimental data.