Optimized depth of field methodology using annular liquid crystal modulator assisted by image processing

Naama Shukrun, Asi Solodar, Amir Aizen, Isaac August, Iftach Klapp, Yitzhak Yitzhaky, Ibrahim Abdulhalim

    Research output: Contribution to journalArticlepeer-review

    2 Scopus citations

    Abstract

    An optical-digital tunable depth of field (DOF) methodology is presented. The suggested methodology forms a fused image based on the sharpest similar depth regions from a set of source images taken with different phase masks. Each phase mask contains a different degree of DOF extension and is implemented by using an annular liquid crystal spatial light modulator, which consists of 16-ring electrodes positioned in the pupil plane. A detailed description of the optical setup and characterization of selected pupil phase masks as well as optimization of the binary phase mask for maximal DOF extension is presented. Experimental results are investigated both qualitatively and quantitatively. In addition, the algorithm's results are compared with those of some well-known fusion algorithms and proved its supremacy.

    Original languageEnglish
    Pages (from-to)3764-3772
    Number of pages9
    JournalApplied Optics
    Volume56
    Issue number13
    DOIs
    StatePublished - 1 May 2017

    ASJC Scopus subject areas

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

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