Iterative l1-min algorithm for fixed pattern noise removal in fiber-bundle-based endoscopic imaging

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Department of Biomedical Engineering


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 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.

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Journal of the Optical Society of America A