Improved playback uniformity of random-phase free holograms by pixel separation method

Random-phase free computer-generated holograms offer excellent quality of virtually noise-free playback of low-frequency images, but have limited efficiency in the case of highly contrast binary images with dominant high spatial frequencies. Introduction of weak random phase allows the partial suppression of this problem, but causes strong noise in the outcome. Here we present the influence of pixel separation technique on the uniformity of far field reconstructions from such random-phase free holograms. We show the improved image quality with no additional speckle noise. Full Text: PDF ReferencesJ.W. Goodman, Roberts and Company (2005). DirectLink R.W. Gerchberg, W.O. Saxton, "A practical algorithm for the determination of phase from image and diffraction plane pictures", Optik 35, 237 (1972). DirectLink M. Makowski, "Minimized speckle noise in lens-less holographic projection by pixel separation", Opt. Express 21, 29205 (2013). CrossRef I. Ducin, T. Shimobaba, M. Makowski, K. Kakarenko, A. Kowalczyk, Jaroslaw Suszek, M. Bieda, A. Kolodziejczyk, M. Sypek, "Holographic projection of images with step-less zoom and noise suppression by pixel separation", Opt. Comm. 340, 131 (2015). CrossRef T. Shimobaba, T. Ito, "Random phase-free computer-generated hologram", Opt. Express 23, 9549 (2015). CrossRef T. Shimobaba, T. Kakue, Y. Endo, R. Hirayama, D. Hiyama, S. Hasegawa, Y. Nagahama, M. Sano, M. Oikawa, T. Sugie, T. Ito, "Random phase-free kinoform for large objects", Opt. Express 23, 17269 (2015). CrossRef M. Sypek, "Light propagation in the Fresnel region. New numerical approach", Opt. Comm. 116, 43 (1995). CrossRef K. Matsushima, T. Shimobaba, "Band-Limited Angular Spectrum Method for Numerical Simulation of Free-Space Propagation in Far and Near Fields", Opt. Express 17, 19662 (2009). CrossRef

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Low-Frequency Signal Sampling Method Implemented in a PLC Controller Dedicated to Applications in the Monitoring of Selected Electrical Devices

Electronics ◽

10.3390/electronics10040442 ◽

2021 ◽

Vol 10 (4) ◽

pp. 442

Author(s):

Marcin Jaraczewski ◽

Ryszard Mielnik ◽

Tomasz Gębarowski ◽

Maciej Sułowicz

Keyword(s):

Power System ◽

Reactive Power ◽

Low Frequency ◽

Sampling Frequency ◽

Electrical Signal ◽

Distortion Factor ◽

Electrical Devices ◽

Frequency Sampling ◽

Sampled Signal ◽

Band Limited

High requirements for power systems, and hence for electrical devices used in industrial processes, make it necessary to ensure adequate power quality. The main parameters of the power system include the rms-values of the current, voltage, and active and reactive power consumed by the loads. In previous articles, the authors investigated the use of low-frequency sampling to measure these parameters of the power system, showing that the method can be easily implemented in simple microcontrollers and PLCs. This article discusses the methods of measuring electrical quantities by devices with low computational efficiency and low sampling frequency up to 1 kHz. It is not obvious that the signal of 50–500 Hz can be processed using the sampling frequency of fs = 47.619 Hz because it defies the Nyquist–Shannon sampling theorem. This theorem states that a reconstruction of a sampled signal is only guaranteed possible for a bandlimit fmax < fs, where fmax is the maximum frequency of a sampled signal. Therefore, theoretically, neither 50 nor 500 Hz can be identified by such a low-frequency sampling. Although, it turns out that if we have a longer period of a stable multi-harmonic signal, which is band-limited (from the bottom and top), it allows us to map this band to the lower frequencies, thus it is possible to use the lower sampling ratio and still get enough precise information of its harmonics and rms value. The use of aliasing for measurement purposes is not often used because it is considered a harmful phenomenon. In our work, it has been used for measurement purposes with good results. The main advantage of this new method is that it achieves a balance between PLC processing power (which is moderate or low) and accuracy in calculating the most important electrical signal indicators such as power, RMS value and sinusoidal-signal distortion factor (e.g., THD). It can be achieved despite an aliasing effect that causes different frequencies to become indistinguishable. The result of the research is a proposal of error reduction in the low-frequency measurement method implemented on compact PLCs. Laboratory tests carried out on a Mitsubishi FX5 compact PLC controller confirmed the correctness of the proposed method of reducing the measurement error.

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Temporal evolution of reactive and resistive nonlinear instabilities

Journal of Plasma Physics ◽

10.1017/s0022377800012745 ◽

1987 ◽

Vol 38 (3) ◽

pp. 473-481 ◽

Cited By ~ 3

Author(s):

D. B. Melrose

Keyword(s):

Electron Number Density ◽

Temporal Evolution ◽

Random Phase ◽

Low Frequency ◽

Rate Of Change ◽

Number Density ◽

Wave Instability ◽

Langmuir Waves ◽

Secular Evolution ◽

Coherent Wave

A kinetic theory for nonlinear processes involving Langmuir waves, developed in an earlier paper, is extended through consideration of three aspects of the temporal evolution, (i) Following Falk & Tsytovich (1975). the dynamic equation for the rate of change of one amplitude at t is expressed as an integral over T of the product of two amplitudes at t – T and a kernel functionf(T); two generalizations of Falk & Tsytovich's form (f(T) ∝ T) that satisfy the requirement f(∞) = 0 are identified, (ii) It is shown that the low-frequency or beat disturbance may be described in terms of fluctuations in the electron number density, and that its time evolution involves an operator that is essentially the inverse of f(t). (iii) The transition from oscillatory evolution in the reactive or ‘coherent-wave’ version of the three-wave instability to the secular evolution of the resistive or ‘random-phase’ version is discussed qualitatively.

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Application of complex-trace analysis to seismic data for random-noise suppression and temporal resolution improvement

Geophysics ◽

10.1190/1.2196875 ◽

2006 ◽

Vol 71 (3) ◽

pp. V79-V86 ◽

Cited By ~ 19

Author(s):

Hakan Karsli ◽

Derman Dondurur ◽

Günay Çifçi

Keyword(s):

Seismic Data ◽

Trace Analysis ◽

Noise Suppression ◽

Single Channel ◽

Random Noise ◽

Synthetic Data ◽

Low Frequency ◽

Bright Spot ◽

Phase Information ◽

Resolution Improvement

Time-dependent amplitude and phase information of stacked seismic data are processed independently using complex trace analysis in order to facilitate interpretation by improving resolution and decreasing random noise. We represent seismic traces using their envelopes and instantaneous phases obtained by the Hilbert transform. The proposed method reduces the amplitudes of the low-frequency components of the envelope, while preserving the phase information. Several tests are performed in order to investigate the behavior of the present method for resolution improvement and noise suppression. Applications on both 1D and 2D synthetic data show that the method is capable of reducing the amplitudes and temporal widths of the side lobes of the input wavelets, and hence, the spectral bandwidth of the input seismic data is enhanced, resulting in an improvement in the signal-to-noise ratio. The bright-spot anomalies observed on the stacked sections become clearer because the output seismic traces have a simplified appearance allowing an easier data interpretation. We recommend applying this simple signal processing for signal enhancement prior to interpretation, especially for single channel and low-fold seismic data.

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Angular spectrum description of light propagation in planar diffractive optical elements

10.1117/12.544471 ◽

2004 ◽

Author(s):

Rosemarie Hild

Keyword(s):

Light Propagation ◽

Angular Spectrum ◽

Diffractive Optical Elements ◽

Optical Elements

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Low-frequency swell noise suppression based on U-Net

Applied Geophysics ◽

10.1007/s11770-020-0825-7 ◽

2020 ◽

Vol 17 (3) ◽

pp. 419-431

Author(s):

Rui-qi Zhang ◽

Peng Song ◽

Bao-hua Liu ◽

Xiao-bo Zhang ◽

Jun Tan ◽

...

Keyword(s):

Noise Suppression ◽

Low Frequency

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Speckle noise suppression of digital holographic microscopy with diffusion glass rotation

10.1117/12.2605353 ◽

2021 ◽

Author(s):

Bingcai Liu ◽

Rui Niu ◽

Ailing Tian ◽

Hongjun Wang ◽

Xueliang Zhu ◽

...

Keyword(s):

Noise Suppression ◽

Speckle Noise ◽

Digital Holographic Microscopy ◽

Holographic Microscopy

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Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

Journal of Neurophysiology ◽

10.1152/jn.00366.2012 ◽

2012 ◽

Vol 108 (10) ◽

pp. 2837-2845 ◽

Cited By ~ 5

Author(s):

Go Ashida ◽

Kazuo Funabiki ◽

Paula T. Kuokkanen ◽

Richard Kempter ◽

Catherine E. Carr

Keyword(s):

Neural Circuit ◽

Signal To Noise Ratio ◽

Phase Locking ◽

Low Frequency ◽

Membrane Potentials ◽

Signal To Noise ◽

Theoretical Predictions ◽

Noise Ratio ◽

Band Limited

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245–15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274–2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

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