No-reference visually significant blocking artifact metric for natural scene images

Quantifying visually annoying blocking artifacts is essential for image and video quality assessment. This paper presents a no-reference technique that uses the multi neural channels aspect of human visual system (HVS) to quantify visual impairment by altering the outputs of these sensory channels independently using statistical ''standard score'' formula in the Fourier domain. It also uses the bit patterns of the least significant bits (LSB) to extract blocking artifacts. Simulation results show that the blocking artifact extracted using this approach follows subjective visual interpretation of blocking artifacts. This paper also presents a visually significant blocking artifact metric (VSBAM) along with some experimental results.

[1]  J. Robson,et al.  Spatial-frequency channels in human vision. , 1971, Journal of the Optical Society of America.

[2]  Avideh Zakhor,et al.  An optimization approach for removing blocking effects in transform coding , 1995, IEEE Trans. Circuits Syst. Video Technol..

[3]  Alan C. Bovik,et al.  . Efficient DCT-domain blind measurement and reduction of blocking artifacts , 2002, IEEE Trans. Circuits Syst. Video Technol..

[4]  T. Vlachos,et al.  Detection of blocking artifacts in compressed video , 2000 .

[5]  Alan C. Bovik,et al.  Blind quality assessment of JPEG2000 compressed images using natural scene statistics , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[6]  Jun Huang,et al.  Text detection and restoration in natural scene images , 2007, J. Vis. Commun. Image Represent..

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

[8]  Yongmin Kim,et al.  A de-blocking algorithm and a blockiness metric for highly compressed images , 2002, IEEE Trans. Circuits Syst. Video Technol..

[9]  Athanasios Leontaris,et al.  Quality Evaluation of Motion-Compensated Edge Artifacts in Compressed Video , 2007, IEEE Transactions on Image Processing.

[10]  Taejeong Kim,et al.  Noise estimation for blocking artifacts reduction in DCT coded images , 2000, IEEE Trans. Circuits Syst. Video Technol..

[11]  H.R. Wu,et al.  A generalized block-edge impairment metric for video coding , 1997, IEEE Signal Processing Letters.

[12]  Eero P. Simoncelli,et al.  Natural image statistics and divisive normalization: Modeling nonlinearity and adaptation in cortical neurons , 2002 .

[13]  Christoph Kayser,et al.  Temporal Correlations of Orientations in Natural Scenes , 2002, Neurocomputing.

[14]  Shan Suthaharan Perceptual quality metric for digital video coding , 2003 .