Objective Video Quality Method Based on Mutual Information and Human Visual System

In this paper we present the objective video quality metric based on mutual information and Human Visual System. The calculation of proposed metric consists of two stages. In the first stage of quality evaluation whole original and test sequence are pre-processed by the Human Visual System. In the second stage we calculate mutual information which has been utilized as the quality evaluation criteria. The mutual information was calculated between the frame from original sequence and the corresponding frame from test sequence. For this testing purpose we choose Foreman video at CIF resolution. To prove reliability of our metric were compared it with some commonly used objective methods for measuring the video quality. The results show that presented objective video quality metric based on mutual information and Human Visual System provides relevant results in comparison with results of other objective methods so it is suitable candidate for measuring the video quality.

[1]  Yubing Wang,et al.  Survey of Objective Video Quality Measurements , 2006 .

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

[3]  R. Gray Entropy and Information Theory , 1990, Springer New York.

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

[5]  Stefan Winkler,et al.  Digital Video Quality: Vision Models and Metrics , 2005 .

[6]  James Hu,et al.  DVQ: A digital video quality metric based on human vision , 2001 .

[7]  Bülent Sankur,et al.  Statistical evaluation of image quality measures , 2002, J. Electronic Imaging.

[8]  Truong Q. Nguyen,et al.  A perceptual metric for blind measurement of blocking artifacts with applications in transform-block-based image and video coding , 2008, 2008 15th IEEE International Conference on Image Processing.

[9]  Reginald L. Lagendijk,et al.  Perceptual image quality based on a multiple channel HVS model , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[10]  Francisco M. Delicado Martínez,et al.  Objective video quality metrics: A performance analysis , 2006, 2006 14th European Signal Processing Conference.

[11]  H. R. Wu,et al.  Human visual system based objective digital video quality metrics , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[12]  Rajendra Tiwari,et al.  Dental X-ray Image Enhancement Based on Human Visual System and Local Image Statistics , 2006, IPCV.

[13]  Leonidas J. Guibas,et al.  The Earth Mover's Distance as a Metric for Image Retrieval , 2000, International Journal of Computer Vision.