A projection‐based image quality measure

Objective image quality measure, evaluating the image quality consistently with human perception automatically, could be employed in image and video retrieval. And the measure with high efficiency and low computational complexity plays an important role in numerous image and video processing applications. On the assumption that any image's distortion could be modeled as the difference between the projection‐based values (PV) of reference image and the counterpart of distorted image, we propose a new objective quality assessment method based on signal projection for full reference model. The proposed metric is developed by simple parameters to achieve high efficiency and low computational complexity. Experimental results show that the proposed method is well consistent with the subjective quality score. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 94–100, 2008

[1]  Chun-Hsien Chou,et al.  A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile , 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

[2]  Azeddine Beghdadi,et al.  A new image distortion measure based on wavelet decomposition , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[3]  Paul S. Fisher,et al.  A Survey of Quality Measures for Gray Scale Image Compression , 1993 .

[4]  Rong Zhang,et al.  Quality Assessment for Image Coding Based on Matching Pursuit , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[5]  Zhou Wang,et al.  Why is image quality assessment so difficult? , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

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

[7]  Hocine Cherifi,et al.  A comparison of image quality models and metrics based on human visual sensitivity , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[8]  L. Pratap Reddy,et al.  Image Quality Assessment Complemented with Visual Regions of Interest , 2007, 2007 International Conference on Computing: Theory and Applications (ICCTA'07).

[9]  Patrick C. Teo,et al.  Perceptual image distortion , 1994, Electronic Imaging.

[10]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[11]  Ahmet M. Eskicioglu,et al.  An SVD-based grayscale image quality measure for local and global assessment , 2006, IEEE Transactions on Image Processing.

[12]  Alan C. Bovik,et al.  A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms , 2006, IEEE Transactions on Image Processing.

[13]  Xuelong Li,et al.  Direct kernel biased discriminant analysis: a new content-based image retrieval relevance feedback algorithm , 2006, IEEE Transactions on Multimedia.

[14]  Zhou Wang,et al.  Quality-aware images , 2006, IEEE Transactions on Image Processing.

[15]  Xuelong Li,et al.  Negative Samples Analysis in Relevance Feedback , 2007, IEEE Transactions on Knowledge and Data Engineering.

[16]  Nick G. Kingsbury,et al.  A distortion measure for blocking artifacts in images based on human visual sensitivity , 1995, IEEE Trans. Image Process..

[17]  Haim Lefkovitz.  Fundamentals of sensation and perception, 3rd ed , 2001 .

[18]  Andrew B. Watson,et al.  DCT quantization matrices visually optimized for individual images , 1993, Electronic Imaging.

[19]  Xuelong Li,et al.  Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  W. J. Tam,et al.  Image quality measurement by using digital watermarking , 2003, The 2nd IEEE Internatioal Workshop on Haptic, Audio and Visual Environments and Their Applications, 2003. HAVE 2003. Proceedings..

[21]  Xuelong Li,et al.  Which Components are Important for Interactive Image Searching? , 2008, IEEE Transactions on Circuits and Systems for Video Technology.