A Novel No-Reference Perceptual Blur Metric

Abstract:

In this paper, we present a novel no-reference blur metric for images. The blur metric is based on analyzing image features include the mean value of phase congruency image, the entropy of phase congruency image and the distorted image, and the gradient of the distorted image. The new index does NOT need any information from reference image, and image quality estimation is accomplished by simple functional relationship between those features. Our experimental results show that the new index outperforms existing popular no-reference blurriness metric and full reference PSNR on LIVE Gaussian blurred database and IVC blurring images.

• Periodical: Applied Mechanics and Materials (Volumes 568-570)
• Pages: 716-720
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.568-570.716
• Online since: June 2014
• Authors: Chao Feng Li, Yi Wen Ju, Quan Lin Hou
• Keywords: Assessment, Blur Metric, Entropy, Image Quality, No-Reference, Phase Congruency

References

[1] M. Pedersen, J.Y. Hardeberg, Full-Reference Image Quality Metrics, Now Publishers, Incorporated, (2012).

[2] C.T. Vu, T.D. Phan, and D.M. Chandler, S3: A spectral and spatial measure of local perceived sharpness in natural images, IEEE Transactions on Image Processing, 21(3), (2012).

DOI: 10.1109/tip.2011.2169974

[3] N. D. Narvekar, L. J. Karam, A no-reference image blur metric based on the cumulative probability of blur detection (CPBD) [J]. IEEE Transactions on Image Processing, 20(9): 2678-2683, (2011).

DOI: 10.1109/tip.2011.2131660

[4] H. Liu, J. Wang, J. Redi, P. L. Callet, and I. Heynderickx, An efficient no-reference metric for perceived blur, European Workshop on Visual Information Processing, EUVIP 2011, Jul (2011).

DOI: 10.1109/euvip.2011.6045525

[5] A. Ciancio, D. Costa, et al. No-reference blur assessment of digital pictures based on multi-feature classifiers. IEEE Trans. Image Processing, 20 (1), pp.64-75, (2011).

DOI: 10.1109/tip.2010.2053549

[6] C. F. Li, W. Yuan, A. C. Bovik and X. Wu, No-reference blur index using blur comparisons. Electronics Letters, 47(17): 962-963, (2011).

DOI: 10.1049/el.2011.0921

[7] S. Wu, W. Lin, Z. Lu, E. P. Ong, S. Yao, Blind blur assessment for vision-based applications, Proc. IEEE, 1-4244-1017-7/07, 1639-1642, (2007).

[8] Rony Ferzli and Lina J. Karam, A No-Reference Objective Image Sharpness Metric Based on the Notion of Just Noticeable Blur (JNB), IEEE Transactions on Image Processing, 18(4), 717-728, (2009).

DOI: 10.1109/tip.2008.2011760

[9] P. Kovesi, Image features from phase congruency, J. Comput Vision Res., vol. 1, no. 3, pp.1-26, (1999).

[10] H.R. Sheikh, Z. Wang, L.K. Cormack and A.C. Bovik, LIVE Image Quality Assessment Database, [online] Available at: http: /live. ece. utexas. edu/research/quality.

[11] VQEG, Final report from the video quality experts group on the validation of objective models of video quality assessment, http: /www. vqeg. org/, Mar. (2000).

[12] Alexandre Ninassi, Patrick Le Callet and Florent Autrusseau. Pseudo No Reference image quality metric using perceptual data hiding, SPIE Electronic Imaging, Human Vision and Electronic Imaging Conference XI, HVEI06, San Jose, USA, January (2006).

DOI: 10.1117/12.650780