No-Reference Image Quality Assessment using Blur and Noise
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
No-Reference Image Quality Assessment using Blur and Noise

Authors: Min Goo Choi, Jung Hoon Jung, Jae Wook Jeon

Abstract:

Assessment for image quality traditionally needs its original image as a reference. The conventional method for assessment like Mean Square Error (MSE) or Peak Signal to Noise Ratio (PSNR) is invalid when there is no reference. In this paper, we present a new No-Reference (NR) assessment of image quality using blur and noise. The recent camera applications provide high quality images by help of digital Image Signal Processor (ISP). Since the images taken by the high performance of digital camera have few blocking and ringing artifacts, we only focus on the blur and noise for predicting the objective image quality. The experimental results show that the proposed assessment method gives high correlation with subjective Difference Mean Opinion Score (DMOS). Furthermore, the proposed method provides very low computational load in spatial domain and similar extraction of characteristics to human perceptional assessment.

Keywords: No Reference, Image Quality Assessment, blur, noise.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1078462

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3885

References:


[1] Z. Wang, A.C. Bovik, and L. Lu, "Why is image quality assessment so difficult?", Proc. IEEE Inter. Conference Acoustics, Speech, and Signal Processing(ICASSP-2002),Vol.4, pp. 3313-3316, Orlando, FL, 13-17 May 2002.
[2] Video Quality Experts Group (VQEG), http://www.vqeg.org.
[3] M. Pinson and S. Wolf, "Comparing subjective video quality testing methodologies", Proceedings of the SPIE, Vol. 5150, pp. 573-582, 2003.
[4] Z.M. Parvez Sauzzad, Y. Kawayoke, and Y. Horita, "No reference image quality assessment for JPEG2000 based on spatial features", Signal Process: Image Communication 23 (2008) pp.257-268.
[5] R. Venkatesh Babu, S. Suresh, and Andrew Perkis, "No-reference JPEG-image quality assessment using GAP-RBF", Signal Processing 87 (2007) pp.1493-1503
[6] Z. Wang, H.R. Sheikh, and A.C. Bovik, "No-reference perceptual quality assessment of JPEG compressed images", Proceedings of the ICIP,02, vol. 1, pp. 477-480, 2002
[7] H.R. Sheikh, Z. Wang, L. Cormack and A.C. Bovik, "LIVE Image Quality Assessment Database Release 2", http://live.ece.utexas.edu/research/quality.
[8] P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, "Perceptual blur and ringing metrics: application to JPEG2000", Signal Process: Image Communication 19 (2004) pp.163-172.