Principles and techniques of digital holographic microscopy
By Myung K. Kim. 2010
822 citations recorded by the source corpus.
Digital holography is an emerging field of new paradigm in general imaging applications. We present a review of a subset of the research and development activities in digital holography, with emphasis on microscopy techniques and applications. First, the basic results from the general theory of holography, based on the scalar diffraction theory, are summarized, and a general description of the digital holographic microscopy process is given, including quantitative phase microscopy. Several numerical diffraction methods are described and compared, and a number of representative configurations used in digital holography are described, including off-axis Fresnel, Fourier, image plane, in-line, Gabor, and phase-shifting digital holographies. Then we survey numerical techniques that give rise to unique capabilities of digital holography, including suppression of dc and twin image terms, pixel resolution control, optical phase unwrapping, aberration compensation, and others. A survey is also given of representative application areas, including biomedical microscopy, particle field holography, micrometrology, and holographic tomography, as well as some of the special techniques, such as holography of total internal reflection, optical scanning holography, digital interference holography, and heterodyne holography. The review is intended for students and new researchers interested in developing new techniques and exploring new applications of digital holography.
Subfields: Atomic and Molecular Physics, and Optics, Media Technology, Radiation
View Paper: https://www.semanticscholar.org/paper/2d47997e4620fd95a2effe030dfe95bc0a0fc3bb
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In Atomic and Molecular Physics, and Optics
In Media Technology
In Radiation
Citations in the corpus
- Principles of interference microscopy for the measurement of surface topography (2015, neutral): “Holographic microscopy has evolved to a flexible quantitative technique encompassing the characterization of surface structures [48,49].”
- Lensless computational imaging through deep learning (2017, methodology): “Our experimental arrangement, described in more detail in Section 2, falls in-between two categories of imaging systems that could be traditionally called "digital holographic imaging,” [28] and “transport-of-intensity imaging” [12, 15].”