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Accuracy of Axial Localization of Particles from In-Line Hologram by Wavelet Transforms

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In the digital holography applied to particle localization, the depth of focus of the holographic process limits the axial resolution. The wavelet technique, based on the direct analysis of the particles hologram, makes it possible to find the axial location of the particles without going through the reconstruction process. The principle of this technique consists in the frequency analysis of the interference fringes of the particles hologram. In practice, it is found that the measurement accuracy of the local frequency also depends on the size of the particles, which affects the axial resolution. A numerical simulation study shows this phenomenon which resembles the effect of the depth of focus in the holographic reconstruction process.
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Digital In-Line Holography; Wavelet Transform Applied to Particle Measurement

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B. J. Thompson, J. H. Ward, and W. R. Zinky, Application of hologram techniques for particle size analysis, Appl. Opt, vol. 6 (Issue 3): 519-526 (1967).

L. Onural and M. T. Özgen, Extraction of three-dimensional object-location information directly from in-line holograms using Wigner analysis, J. Opt. Soc. Am. A, vol. 9 (Issue 2): 252-260, (1992).

L. Onural, Diffraction from a wavelet point of view, Opt. Lett., vol. 18 (Issue1):846-848, (June 1993).

W. L. Anderson and H. Diao, Two-dimensional wavelet transform and application to holographic particle velocimetry, Appl. Opt., vol. 34(Issue 10): 249-255, (January 1995).

S. Belaïd, D. Lebrun, C. Özkul, Application of two-dimensional wavelet transform to hologram analysis: visualization of glass fibres in turbulent flame, Opt. Eng., vol. 36 (Issue 103): 1947-1951, (July 1997).

Siriwat Soontaranon, Joewono Widjaja, Toshimitsu Asakura, Direct analysis of in-line particle holograms by using wavelet transform and envelope reconstruction method, Optik, vol 113, (Issue 11):489-494,(January 2002).

Wafa, R., Mbainaibeye, J., Image Modeling Based on Complex Wavelet Decomposition: Application to Image Compression and Texture Analysis, (2017) International Review on Computers and Software (IRECOS), 12 (1), pp. 1-20.

Hasan Abbas, N., Syed Ahmad, S., Wan Adnan, W., Bin Ramli, A., Parveen, S., DWT and Lifting Wavelet Transform Based Robust Watermarking for Color Image, (2015) International Review on Computers and Software (IRECOS), 10 (11), pp. 1127-1133.

El-Samad, S., Obeid, O., Zaharia, G., Sadek, S., El Zein, G., Remote Heartbeat Detection Using Microwave System from Four Positions of a Normally Breathing Patient, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (3), pp. 175-181.

G. A. Tyler, B. J. Thompson, Fraunhofer holography applied to particle size analysis a reassessement, Optice Acta, vol 23 (Issue 9): 685-700, (April 1976).

L. Onural, P. D. Scott, Digital decoding of in-line holograms, Optial Engeneering, vol 26 (Issue 11):1124-1132, (November 1987).

T. Colomb et al., Extended depth-of-focus by digital holographic microscopy, Optic letters, vol. 35 (Issue 11): 1840-1842, (June 2010)

Murata, H. Fujiwara, T. Asakura: Several problems in in-line Fraunhofer holography for bubble chamber track recording, Cambridge University Conference on Engineering Use of holography, 289-300. (1970).

S. Mallat, A Wavelet tour of signal processing,(Academic Press, Elsevier, 1999).

Kronland-Martinet, J. Morlet, A. Crossmann, Analysis of sound patterns through wavelet transforms, Int. J. Patt. Recog. Artificial Intell. vol1, (Issue2):273-302 (January 1987).

Thanh Viet, D., Huu Hieu, N., Minh Khoa, N., A Method for Monitoring Voltage Disturbances Based on Discrete Wavelet Transform and Adaptive Linear Neural Network, (2016) International Review of Electrical Engineering (IREE), 11 (3), pp. 314-322.

Hendradi, R., Arifin, A., Shida, H., Gunawan, S., Purnomo, M., Hasegawa, H., Kanai, H., Signal Processing and Extensive Characterization Method of Heart Sounds Based on Wavelet Analysis, (2016) International Review of Electrical Engineering (IREE), 11 (1), pp. 55-68.

Bazi, S., Nait Said, M., Extreme Learning Machines and Particle Swarm Optimization for Induction Motor Faults Detection and Classification, (2015) International Review of Electrical Engineering (IREE), 10 (4), pp. 501-509.

Batischev, V., Kuzmin, M., Pischukhin, A., Solovyov, N., System of Computer Vision for Cold-Rolled Metal Quality Control, (2016) International Review of Automatic Control (IREACO), 9 (4), pp. 259-263.

Kaddar, B., Fizazi, H., Spatiotemporal Analysis for NDVI Time Series Using Local Binary Pattern and Daubechies Wavelet Transform, (2017) International Review of Aerospace Engineering (IREASE), 10 (2), pp. 96-104.

Agboje, O., Idowu-Bismark, O., Ibhaze, A., Comparative Analysis of Fast Fourier Transform and Discrete Wavelet Transform Based MIMO-OFDM, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (2), pp. 168-175.

Udaya Kumar, N., Krishna Rao V., E., Madhavi Latha, M., Multi Directional Wavelet Filter Based Region of Interest Compression for Low Resolution Images, (2015) International Journal on Communications Antenna and Propagation (IRECAP), 5 (2), pp. 54-62.


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