Iterative I1-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging

Xuan Liu, Lijun Zhang, Mitchell Kirby, Richard Becker, Shaohai Qi, Feng Zhao

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this study, we developed a signal processing method for fixed pattern noise removal in fiber-bundle-based endoscopic imaging. We physically acquired the fixed pattern of the fiber bundle and used it as a prior image in an l1 norm minimization (l1-min) algorithm. We chose an iterative shrinkage thresholding algorithm for l1 norm minimization. In addition to fixed pattern noise removal, this method also improved image contrast while preserving spatial resolution. The effectiveness of this method was demonstrated on images obtained from a darkfield illuminated reflectance fiber-optic microscope (DRFM). The iterative l1-min algorithm presented in this paper, in combination with the DRFM system that we previously developed, enables high-resolution, highsensitivity, intrinsic-contrast, and in situ cellular imaging which has great potential in clinical diagnosis and biomedical research.

Original languageEnglish (US)
Pages (from-to)630-636
Number of pages7
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume33
Issue number4
DOIs
StatePublished - Apr 2016

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Iterative I<sub>1</sub>-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging'. Together they form a unique fingerprint.

Cite this