Improving principal component analysis based phase extraction method for phase-shifting interferometry by integrating spatial information

Kohei Yatabe, Kenji Ishikawa, Yasuhiro Oikawa

    Research output: Contribution to journalArticle

    25 Citations (Scopus)

    Abstract

    Phase extraction methods based on the principal component analysis (PCA) can extract objective phase from phase-shifted fringes without any prior knowledge about their shift steps. Although it is fast and easy to implement, many fringe images are needed for extracting the phase accurately from noisy fringes. In this paper, a simple extension of the PCA method for reducing extraction error is proposed. It can effectively reduce influence from random noise, while most of the advantages of the PCA method is inherited because it only modifies the construction process of the data matrix from fringes. Although it takes more time because size of the data matrix to be decomposed is larger, computational time of the proposed method is shown to be reasonably fast by using the iterative singular value decomposition algorithm. Numerical experiments confirmed that the proposed method can reduce extraction error even when the number of interferograms is small.

    Original languageEnglish
    Pages (from-to)22881-22891
    Number of pages11
    JournalOptics Express
    Volume24
    Issue number20
    DOIs
    Publication statusPublished - 2016 Oct 3

    Fingerprint

    principal components analysis
    interferometry
    matrices
    random noise
    decomposition
    shift

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics

    Cite this

    Improving principal component analysis based phase extraction method for phase-shifting interferometry by integrating spatial information. / Yatabe, Kohei; Ishikawa, Kenji; Oikawa, Yasuhiro.

    In: Optics Express, Vol. 24, No. 20, 03.10.2016, p. 22881-22891.

    Research output: Contribution to journalArticle

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