Iterative l1-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging
Document Type
Article
Publication Date
2-17-2016
Department
Department of Biomedical Engineering
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 π1 norm minimization (π1-min) algorithm. We chose an iterative shrinkage thresholding algorithm for π1 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 dark-field illuminated reflectance fiber-optic microscope (DRFM). The iterative π1-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.
Publication Title
Journal of the Optical Society of America A
Recommended Citation
Liu, X.,
Zhang, L.,
Kirby, M.,
Becker, R.,
Qi, S.,
&
Zhao, F.
(2016).
Iterative l1-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging.
Journal of the Optical Society of America A,
33(4), 630-636.
http://doi.org/10.1364/JOSAA.33.000630
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/1311