Quality Assessment of Gaussian Blurred Images Using Symmetric Geometric Moments

A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the reference and test images. The reference and test images are divided into (8 times 8) blocks and the SGM up to fourth order for each block is computed. SGM of the corresponding blocks of the reference and test images are used to form the correlation index or quality metric of each block. The correlation index of the test image is then obtained by taking the average of all blocks. The performance of the proposed metric is validated through subjective evaluation by comparing with objective methods (PSNR and MSSIM) on a database of 174 Gaussian blurred images. The proposed metric performs better than PSNR and MSSIM by providing larger correlation coefficients and smaller errors after nonlinear regression fitting.

[1]  Zhou Wang,et al.  Reduced-reference image quality assessment using a wavelet-domain natural image statistic model , 2005, IS&T/SPIE Electronic Imaging.

[2]  Thrasyvoulos N. Pappas,et al.  Perceptual criteria for image quality evaluation , 2005 .

[3]  R. SheikhH.,et al.  No-reference quality assessment using natural scene statistics , 2005 .

[4]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[5]  Roland T. Chin,et al.  On image analysis by the methods of moments , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Zhou Wang,et al.  No-reference perceptual quality assessment of JPEG compressed images , 2002, Proceedings. International Conference on Image Processing.

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

[8]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .

[9]  Zhou Wang,et al.  Blind measurement of blocking artifacts in images , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[10]  R. Mukundan,et al.  Moment Functions in Image Analysis: Theory and Applications , 1998 .

[11]  Bernd Girod,et al.  What's wrong with mean-squared error? , 1993 .

[12]  Paul S. Fisher,et al.  Image quality measures and their performance , 1995, IEEE Trans. Commun..

[13]  Alan C. Bovik,et al.  41 OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[14]  A. Bovik,et al.  OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[15]  Alan C. Bovik,et al.  No-reference quality assessment using natural scene statistics: JPEG2000 , 2005, IEEE Transactions on Image Processing.