High-accuracy off-axis wavefront reconstruction from noisy data: local least square with multiple adaptive windows

Vladimir Katkovnik, Igor Shevkunov, Nikolay V. Petrov, Karen Egiazarian

    Research output: Contribution to journalArticleScientificpeer-review

    18 Citations (Scopus)

    Abstract

    A variational algorithm to object wavefront reconstruction from noisy intensity observations is developed for the off-axis holography scenario with imaging in the acquisition plane. The algorithm is based on the local least square technique proposed in paper [J. Opt. Soc. Am. A, 21, 367 (2004)]. First, multiple reconstructions of the wavefront are produced for various size and various directional windows applied for localization of estimation. At the second stage, a special statistical rule is applied in order to select the best window size estimate for each pixel of the image and for each of the directional windows. At the third final stage the estimates of the different directions obtained for each pixel are aggregated in the final one. Simulation experiments and real data processing prove that the developed algorithm demonstrate the performance of the extraordinary quality and accuracy for both the phase and amplitude of the object wavefront. (C) 2016 Optical Society of America

    Original languageEnglish
    Pages (from-to)25068-25083
    Number of pages16
    JournalOptics Express
    Volume24
    Issue number22
    DOIs
    Publication statusPublished - 31 Oct 2016
    Publication typeA1 Journal article-refereed

    Keywords

    • DIGITAL HOLOGRAPHY
    • PHASE
    • MICROSCOPY
    • TRANSFORM

    Publication forum classification

    • Publication forum level 2

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