title: Iterative l(1)-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging.
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 l1norm minimization (l1-min) algorithm. We chose an iterative shrinkage thresholding algorithm for l1norm 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 dark-field 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, high-sensitivity, intrinsic-contrast, and in situ cellular imaging which has great potential in clinical diagnosis and biomedical research.
authors.forename: Xuan
authors.initials: X
authors.lastname: Liu
authors.forename: Lijun
authors.initials: L
authors.lastname: Zhang
authors.forename: Mitchell
authors.initials: M
authors.lastname: Kirby
authors.forename: Richard
authors.initials: R
authors.lastname: Becker
authors.forename: Shaohai
authors.initials: S
authors.lastname: Qi
authors.forename: Feng
authors.initials: F
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D004724:Endoscopy / Q000295:instrumentation*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D059630:Mesenchymal Stem Cells / Q000166:cytology; D055100:Optical Fibers; D059629:Signal-To-Noise Ratio