Abstract
An adaptive filtering method for off-axis digital holographic reconstruction is presented. The spatial spectrum distribution of an off-axis digital hologram is clustered based on the K-means clustering algorithm of unsupervised machine learning . The spatial-spectrum filtering can be carried out by the quantitative comparison of different filtering interception windows. The first-order spectrum including the object information can be automatically located and intercepted after clustering the spatial spectrum distribution of the hologram. The experiment results demonstrate that the reconstruction images with better resolution and imaging quality can be achieved by the adaptive filtering algorithm. This adaptive filtering reconstruction based on K-means clustering provides a new way of automatic reconstruction imaging for off-axis digital holography.
Published Version
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.
