Fresnelets are wavelet-like base functions specially tailored for digital holography applications. We introduce their use in phase-shifting interferometry (PSI) digital holography for the compression of such holographic data. Two compression methods are investigated. One uses uniform quantization of the Fresnelet coefficients followed by lossless coding, and the other uses set portioning in hierarchical trees (SPIHT) coding. Quantization and lossless coding of the original data is used to compare the performance of the proposed algorithms. The comparison reveals that the Fresnelet transform of phase-shifting holograms in combination with SPIHT or uniform quantization can be used very effectively for the compression of holographic data. The performance of the new compression schemes is demonstrated on real PSI digital holographic data.
Phase-shifting digital hologram compression has been mainly studied in the recording domain, where data possess a rather randomlike appearance, yielding reduced compression efficiency. We carry out the compression of such data in the reconstruction domain, which benefits from the spatial correlation of the data yielding, increased efficiency. Real holographic data are used to demonstrate the performance of the new approach. It is also shown that the reconstruction is not limited to the initially obtained view, as additional views can still be obtained with appropriate postprocessing.
a b s t r a c tDigital holography is an effective 3D imaging technique, with the potential to be used for particle size measurements. A digital hologram can provide reconstructions of volume samples focused at different depths, overcoming the focusing problems encountered by other imaging based techniques. Several particle analysis methods discussed in the literature consider spherical particles only. With the object sphericity assumption in place, analysis of the holographic data can be significantly simplified. However, there are applications, such as particle analysis and crystallization monitoring, where non-spherical particles are often encountered. This paper discusses the processing of digital holograms for particle size and shape measurement for both spherical and arbitrarily shaped particles. An automated algorithm for identification of particles from recorded hologram and subsequent size and shape measurement is described. Experimental results using holograms of spherical and non-spherical particles demonstrate the performance of the proposed measuring algorithm.
Abstract:A method to measure the size, orientation, and location of opaque micro-fibers using digital holography is presented. The method involves the recording of a digital hologram followed by reconstruction at different depths. A novel combination of automated image analysis and statistical techniques, applied on the intensity of reconstructed digital holograms is used to accurately determine the characteristics of the microfibers. The performance of the proposed method is verified with a single fiber of known length and orientation. The potential of the method for measurement of fiber length is further demonstrated through its application to a suspension of fibers in a liquid medium.
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