Visual attention based image quality assessment

Inspired by the success of structural similarity index (SSIM), some image quality assessment (IQA) methods have been developed recently. To achieve better performance, this paper proposes a new visual attention (VA) model that combines saliency based VA and visual importance based VA, under the assumptions that humans often pay more attention to the regions with important content in the beginning of evaluating a given image and then the regions with poor quality. Then the proposed VA model is incorporated into SSIM. The experiments on LIVE database and TID2008 database demonstrate its improvements over the latest state-of-the-art IQA methods and the information content weighted SSIM measure (IW-SSIM).

[1]  Zhou Wang,et al.  Multi-scale structural similarity for image quality assessment , 2003 .

[2]  Alan C. Bovik,et al.  Visual Importance Pooling for Image Quality Assessment , 2009, IEEE Journal of Selected Topics in Signal Processing.

[3]  Liming Zhang,et al.  Image quality assessment with visual attention , 2008, 2008 19th International Conference on Pattern Recognition.

[4]  Debin Zhao,et al.  Fovea based image quality assessment , 2010, Visual Communications and Image Processing.

[5]  Zhou Wang,et al.  Spatial Pooling Strategies for Perceptual Image Quality Assessment , 2006, 2006 International Conference on Image Processing.

[6]  Zhou Wang,et al.  Translation insensitive image similarity in complex wavelet domain , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[7]  Liqing Zhang,et al.  Saliency Detection: A Spectral Residual Approach , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Lai-Man Po,et al.  Edge-Based Structural Similarity for Image Quality Assessment , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[9]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[10]  Alan C. Bovik,et al.  Unifying analysis of full reference image quality assessment , 2008, 2008 15th IEEE International Conference on Image Processing.

[11]  Zhou Wang,et al.  Multiscale structural similarity for image quality assessment , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[12]  Zhong Liu,et al.  Perceptual image quality assessment using a geometric structural distortion model , 2010, 2010 IEEE International Conference on Image Processing.

[13]  Alan C. Bovik,et al.  Image information and visual quality , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[14]  Zhou Wang,et al.  Information Content Weighting for Perceptual Image Quality Assessment , 2011, IEEE Transactions on Image Processing.