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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 3, Iss. 1 — Jan. 29, 2008

Blind image quality assessment through anisotropy

Salvador Gabarda and Gabriel Cristóbal  »View Author Affiliations


JOSA A, Vol. 24, Issue 12, pp. B42-B51 (2007)
http://dx.doi.org/10.1364/JOSAA.24.000B42


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Abstract

We describe an innovative methodology for determining the quality of digital images. The method is based on measuring the variance of the expected entropy of a given image upon a set of predefined directions. Entropy can be calculated on a local basis by using a spatial/spatial-frequency distribution as an approximation for a probability density function. The generalized Rényi entropy and the normalized pseudo-Wigner distribution (PWD) have been selected for this purpose. As a consequence, a pixel-by-pixel entropy value can be calculated, and therefore entropy histograms can be generated as well. The variance of the expected entropy is measured as a function of the directionality, and it has been taken as an anisotropy indicator. For this purpose, directional selectivity can be attained by using an oriented 1-D PWD implementation. Our main purpose is to show how such an anisotropy measure can be used as a metric to assess both the fidelity and quality of images. Experimental results show that an index such as this presents some desirable features that resemble those from an ideal image quality function, constituting a suitable quality index for natural images. Namely, in-focus, noise-free natural images have shown a maximum of this metric in comparison with other degraded, blurred, or noisy versions. This result provides a way of identifying in-focus, noise-free images from other degraded versions, allowing an automatic and nonreference classification of images according to their relative quality. It is also shown that the new measure is well correlated with classical reference metrics such as the peak signal-to-noise ratio.

© 2007 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.6640) Image processing : Superresolution
(110.3000) Imaging systems : Image quality assessment
(330.6180) Vision, color, and visual optics : Spectral discrimination

History
Original Manuscript: February 26, 2007
Revised Manuscript: July 9, 2007
Manuscript Accepted: July 18, 2007
Published: September 26, 2007

Virtual Issues
Vol. 3, Iss. 1 Virtual Journal for Biomedical Optics

Citation
Salvador Gabarda and Gabriel Cristóbal, "Blind image quality assessment through anisotropy," J. Opt. Soc. Am. A 24, B42-B51 (2007)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-24-12-B42

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