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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 18, Iss. 7 — Mar. 29, 2010
  • pp: 7138–7149

Novel Bayesian deringing method in image interpolation and compression using a SGLI prior

Cheolkon Jung and Licheng Jiao  »View Author Affiliations


Optics Express, Vol. 18, Issue 7, pp. 7138-7149 (2010)
http://dx.doi.org/10.1364/OE.18.007138


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Abstract

This paper provides a novel Bayesian deringing method to reduce ringing artifacts caused by image interpolation and JPEG compression. To remove the ringing artifacts, the proposed method uses a Bayesian framework based on a SGLI (spatial-gradient-local-inhomogeneity) prior. The SGLI prior employs two complementary discontinuity measures: spatial gradient and local inhomogeniety. The spatial gradient measure effectively detects strong edge components in images. In addition, the local inhomogeniety measure successfully detects locations of the significant discontinuities by taking uniformity of small regions into consideration. The two complementary measures are elaborately combined to create prior probabilities of the Bayesian deringing framework. Thus, the proposed deringing method can effectively preserve the significant discontinuities such as textures of objects as well as the strong edge components in images while reducing the ringing artifacts. Experimental results show that the proposed deringing method achieves average PSNR gains of 0.09 dB in image interpolation artifact reduction and 0.21 dB in JPEG compression artifact reduction.

© 2010 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(100.3020) Image processing : Image reconstruction-restoration

ToC Category:
Image Processing

History
Original Manuscript: January 20, 2010
Revised Manuscript: March 12, 2010
Manuscript Accepted: March 14, 2010
Published: March 23, 2010

Citation
Cheolkon Jung and Licheng Jiao, "Novel Bayesian deringing method 
in image interpolation and compression 
using a SGLI prior," Opt. Express 18, 7138-7149 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-7-7138


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