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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 8 — Apr. 21, 2014
  • pp: 10046–10063

Texture analysis microscopy: quantifying structure in low-fidelity images of dense fluids

Yongxiang Gao and Matthew E. Helgeson  »View Author Affiliations

Optics Express, Vol. 22, Issue 8, pp. 10046-10063 (2014)

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Optical images are often corrupted by noise, low contrast, uneven illumination and artefacts, which may pose significant challenges to image analysis, particularly for dense fluids. Traditionally, noise removal and contrast enhancement are achieved by global arithmetic operations on the image as a whole, and/or by image convolution with various kernels. However, these methods work under very limited conditions and can compromise detail within the image. Here, we develop a new technique, texture analysis microscopy (TAM), to overcome these challenges based on the method of image correlation. TAM recasts an image by the statistical similarities between a raw image and a template feature (e.g. a Gaussian) that best approximates features in the image. We demonstrate the superiority of TAM by applying it to low-fidelity images under conditions where traditional methods fail or have deteriorative performance, for analyses including structural correlations, particle identification and sizing.

© 2014 Optical Society of America

OCIS Codes
(070.4790) Fourier optics and signal processing : Spectrum analysis
(100.2960) Image processing : Image analysis
(100.2980) Image processing : Image enhancement
(180.0180) Microscopy : Microscopy
(100.4999) Image processing : Pattern recognition, target tracking

ToC Category:

Original Manuscript: February 18, 2014
Revised Manuscript: March 25, 2014
Manuscript Accepted: March 28, 2014
Published: April 18, 2014

Virtual Issues
Vol. 9, Iss. 6 Virtual Journal for Biomedical Optics

Yongxiang Gao and Matthew E. Helgeson, "Texture analysis microscopy: quantifying structure in low-fidelity images of dense fluids," Opt. Express 22, 10046-10063 (2014)

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