Abstract
A novel random field computational adaptive optics (R-CAO) framework is proposed to jointly correct for optical aberrations and speckle noise issues in optical coherence microscopy (OCM) and thus overcome the depth-of-field limitation in OCM imaging. The performance of the R-CAO approach is validated using OCM tomograms acquired from a standard USAF target and a phantom comprised of 1 \({\upmu }\)m diameter microspheres embedded in agar gel. The R-CAO reconstructed OCM tomograms show reduced optical aberrations and speckle noise over the entire depth of imaging compared to the existing state-of-the-art computational adaptive optics algorithms such as the regularized maximum likelihood computational adaptive optics (RML-CAO) method. The reconstructed images using the proposed R-CAO framework show the usefulness of this method for the quality enhancement of OCM imaging over different imaging depths.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
