Fractal description of rough surfaces

Angelsky, Oleg V.; Burkovets, Dmitry N.; Koval’chuk, A. V.; Hanson, Steen Grüner

doi:10.1364/ao.41.004620

Cited by 44 publications

(23 citation statements)

References 12 publications

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“…It is conceived that micro-and nanoparticle manipulation would widen the application of correlation methods of analyzing fractal objects [26][27][28][29] , including objects of biological origin 30 .…”

Section: Resultsmentioning

confidence: 99%

Circular motion of particles by the help of the spin part of the internal energy flow

et al. 2013

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Non-spherical dielectric microparticles were suspended in the water-filled cell and exposed to the coherent Gaussian light beam with switchable state of polarization. When the beam polarization is linear, the particles were trapped at certain off-axial position within the beam cross section. After switching to the right (left) circular polarization, the particles performed spinning motion in agreement with the angular momentum imparted by the field, but also they were involved in the orbital rotation around the beam axis, which in previous works [Y. Zhao et al, Phys. Rev. Lett. 99, 073901 (2007)] was treated as an evidence for the spin-to orbital angular momentum conversion. Since in our situation the moderate focusing of the beam excluded possibility of such a conversion, we treat the observed particle behaviour as a demonstration of the macroscopic "spin energy flow" predicted by the theory of inhomogeneously polarized paraxial beams [A. Bekshaev et al, J. Opt. 13, 053001 (2011)].

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Section: Resultsmentioning

confidence: 99%

Circular motion of particles by the help of the spin part of the internal energy flow

et al. 2013

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“…Such a function was effectively used in [15][16][17][18][19] for analysis of multiscale laser images of rough surfaces and histological sections of biological tissues. This case provides the possibility of comparative analysis of this Table 1: Log-log dependences of power spectra for the wavelet coefficients W a,b of statistical-stochastic distributions for f ik elements of the Mueller matrix describing single-axis biological crystals.…”

Section: Wavelet Analysis Of Mueller-matrix Images Of Biological Tissuesmentioning

confidence: 99%

On the Feasibilities of Using the Wavelet Analysis of Mueller Matrix Images of Biological Crystals

Dubolazov

Ушенко

Bachynsky

et al. 2010

Advances in Optical Technologies

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The efficiency of using the statistical and fractal analyses for distributions of wavelet coefficients for Mueller matrix images of biological crystal networks inherent to human tissues is theoretically grounded in this work. The authors found interrelations between statistical moments and power spectra for distributions of wavelet coefficients as well as orientation-phase changes in networks of biological crystals. Also determined are the criteria for statistical and fractal diagnostics of changes in the birefringent structure of biological crystal network, which corresponds to pathological changes in tissues.

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“…The main information for these methods is obtained from coordinate distributions of polarization azimuths   y x,  and ellipticity   y x,  (polarization maps) with the following correlation (auto-and mutually correlation functions [9,16,37]) and fractal (fractal dimensions [8,11,21,33]) analysis.…”

Section: [11] Introductionmentioning

confidence: 99%