Comparative analysis of gradient-field-based orientation estimation methods and regularized singular-value decomposition for fringe pattern processing

Qi Sun, Shujun Fu

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Fringe orientation is an important feature of fringe patterns and has a wide range of applications such as guiding fringe pattern filtering, phase unwrapping, and abstraction. Estimating fringe orientation is a basic task for subsequent processing of fringe patterns. However, various noise, singular and obscure points, and orientation data degeneration lead to inaccurate calculations of fringe orientation. Thus, to deepen the understanding of orientation estimation and to better guide orientation estimation in fringe pattern processing, some advanced gradient-field-based orientation estimation methods are compared and analyzed. At the same time, following the ideas of smoothing regularization and computing of bigger gradient fields, a regularized singular-value decomposition (RSVD) technique is proposed for fringe orientation estimation. To compare the performance of these gradient-field-based methods, quantitative results and visual effect maps of orientation estimation are given on simulated and real fringe patterns that demonstrate that the RSVD produces the best estimation results at a cost of relatively less time.

    Original languageEnglish (US)
    Pages (from-to)7708-7717
    Number of pages10
    JournalApplied Optics
    Volume56
    Issue number27
    DOIs
    StatePublished - Sep 20 2017

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics
    • Engineering (miscellaneous)
    • Electrical and Electronic Engineering

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