Journal of The Optical Society of America A-optics Image Science and Vision最新文献

This paper serves as part I of a two-part tutorial on "aero-optical effects." We first present background information to assist with our introduction of the topic. Next, we use the aerodynamic environment associated with a hemisphere-on-cylinder beam director to decompose the resulting aberrations (that arise due to aero-optical effects) in terms of piston, tilt, and higher-order phase errors. We also discuss the performance implications that these phase errors have on airborne-laser systems. Recognizing the complexity of these environments, we then discuss how one measures these phase errors using standard wavefront-sensing approaches and the impact these phase errors have on imaging performance. These system-level considerations provide the material needed to survey several sources of aberrations such as boundary layers and shear layers, as well as mechanical contamination, shock waves, and aero-acoustics-all of which we cover in part II of this two-part tutorial.

For given tristimulus values X, Y, Z of the object with reflectance ρ(λ) viewed under an illuminant S(λ) with tristimulus values X ₀, Y ₀, Z ₀, an earlier algorithm constructs the smoothest metameric estimate ρ ₀(λ) under S(λ) of ρ(λ), independent of the amplitude of S(λ). It satisfies a physical property of ρ(λ), i.e., 0≤ρ ₀(λ)≤1, on the visual range. The second inequality secures the condition that for no λ the corresponding patch returns more radiation from S(λ) than is incident on it at λ, i.e., ρ ₀(λ) is a fundamental metameric estimate; ρ ₀(λ) and ρ(λ) differ by an estimation error causing perceptual variables assigned to ρ ₀(λ) and ρ(λ) under S(λ) to differ under the universal reference illuminant E(λ)=1 for all λ, tristimulus values X _E, Y _E, Z _E. This color constancy error is suppressed but not nullified by three narrowest nonnegative achromatic response functions A _i(λ) defined in this paper, replacing the cone sensitivities and invariant under any nonsingular transformation T of the color matching functions, a demand from theoretical physics. They coincide with three functions numerically constructed by Yule apart from an error corrected here. S(λ) unknown to the visual system as a function of λ is replaced by its nonnegative smoothest metameric estimate S ₀(λ) with tristimulus values made available in color rendering calculations, by specular reflection, or determined by any educated guess; ρ(λ) under S(λ) is replaced by its corresponding color R ₀(λ) under S ₀(λ) like ρ(λ) independent of the amplitude of S ₀(λ). The visual system attributes to R ₀(λ)E(λ) one achromatic variable, in the CIE case defined by y(λ)/Y _E, replaced by the narrowest middle wave function A ₂(λ) normalized such that the integral of A ₂(λ)E(λ) over the visual range equals unity. It defines the achromatic variable ξ ₂, A(λ), and ξ as described in the paper. The associated definition of present luminance explains the Helmholtz-Kohlrausch effect in the last figure of the paper and rejects CIE 1924 luminance that fails to do so. It can be understood without the mathematical details.

In this paper, we construct a wireless optical MIMO system based on the ocean power spectrum in the vertical channels, which is suitable for any sea depth under the combined effects of ocean turbulence and pointing errors. Thereby, an adaptive transmit laser selection-optical quadrature spatial modulation (TLS-OQSM) technology is proposed to improve its effectiveness and reliability of communication. The adaptive TLS-OQSM employs the channel adaptive bit mapping (CABM) to grouping and spatial mapping for laser diode (LD) indices based on limited feedback bits for the adaptive signal modulation and power allocation (PA). Simulation results show that the average BER of the system can be efficiently reduced by applying the adaptive TLS-OQSM scheme at different depths in seawater where optical transceivers are deployed, with different pointing errors and different predefined spectral efficiencies.

In this paper, the spectral characteristics formed by a double-grating transmission scheme are discussed based on the scalar diffraction theory. First, considering two different grating periods, the angular spectrum at the back of the second grating is obtained. Then, the spectral characteristics are discussed with three different periodic conditions, while it is proved that the spatial distribution and spacing of the spectrum are absolutely determined by the grating constants and angles. The theoretical results manifest that the spatial distribution range of the spectrum becomes larger as the angle increases, unlike the spectral points, which are distributed on a single line when the grating lines of the two gratings are parallel. Finally, for the sake of proving that our theoretical analysis is correct and reasonable, three sets of experiments are conducted with three different combinations of Ronchi gratings. As expected, the experimental and theoretical results are in perfect agreement. In a word, the involved results could be useful for expanding the application of moiré deflectometry.

Surface plasmon imaging and sensing is a well-established and important technology for the detection of minute binding events in, for instance, antibody/antigen reactions. More recently it has been realized that surface plasmon effects can be used to measure voltages as well as electrical impedance. At first sight the physical mechanisms for binding and voltage sensing appear very different; however, we develop a transmission line and impedance representation of the sensing process which clearly shows that binding and voltage sensing can be conveniently represented in a common framework. Our transmission line model shows graphically how the gold layer amplifies reflectivity changes resulting in optimum sensitivity at around 48 nm gold thickness. The other elegant feature of this representation is that the model clearly shows the role of the change in amplitude and phase in the sensing process; indeed it reveals their relative contribution to the output of the sensor. The graphical representation is also very suggestive of a model to quantify the performance of different detection strategies. This model provides a framework to describe these strategies without reference to any specific noise mechanisms. The results of the model definitively support previous assertions that phase imaging gives better sensitivity compared to intensity measurement. Moreover, we show that measurement of the complex amplitude containing both amplitude and phase of the detected signal performs even better than phase only detection. This opens the way for further enhancements of detection sensitivity.

The digital image correlation method is a non-contact optical measurement method, which has the advantages of full-field measurement, simple operation, and high measurement accuracy. The traditional DIC method can accurately measure displacement and strain fields, but there are still many limitations. (i) In the measurement of large displacement deformations, the calculation accuracy of the displacement field and strain field needs to be improved due to the unreasonable setting of parameters such as subset size and step size. (ii) It is difficult to avoid under-matching or over-matching when reconstructing smooth displacement or strain fields. (iii) When processing large-scale image data, the computational complexity will be very high, resulting in slow processing speeds. In recent years, deep-learning-based DIC has shown promising capabilities in addressing the aforementioned issues. We propose a new, to the best of our knowledge, DIC method based on deep learning, which is designed for measuring displacement fields of speckle images in complex large deformations. The network combines the multi-head attention Swin-Transformer and the high-efficient channel attention module ECA and adds positional information to the features to enhance feature representation capabilities. To train the model, we constructed a displacement field dataset that conformed to the real situation and contained various types of speckle images and complex deformations. The measurement results indicate that our model achieves consistent displacement prediction accuracy with traditional DIC methods in practical experiments. Moreover, our model outperforms traditional DIC methods in cases of large displacement scenarios.

The phase optical transfer function (POTF) is a critical aspect of image formation theory for high-resolution phase imaging such as spatial light interference microscopy. However, current analytic formulae for the POTF do not match experimental results. Further, when used for deconvolution, halo artifacts still persist, and the contrast improvement is rather limited. We hypothesize that one of the reasons for this is that, during the derivation of POTF, the objective is assumed to focus at a plane outside of the sample. In this work, we have derived a new, to the best of our knowledge, POTF assuming that the objective is focused at a plane inside the sample (iPOTF), which more closely matches experimental results. When used for deconvolution, iPOTF not only leads to higher contrast of dim structures but also reduces halos compared with the traditional POTF.

Transport within cells is commonly studied using particle tracking methods. However, these typically require either labeling or identification of specific organelles that can be identified and tracked from label-free imaging modalities, limiting application of this approach. Quantitative phase imaging (QPI) provides dynamic data on the redistribution of mass within live cells, potentially enabling broader application of particle tracking methods. In previous work, we developed quantitative phase velocimetry (QPV) to automatically track the motion of subcellular control volumes from QPI data. However, the relationship of QPV to traditional particle tracking methods has not been established. Here, we directly compare QPV to manual particle tracking across multiple drug treatment conditions. We find that QPV effective diffusivity is correlated with diffusivity measured from manual particle tracking. The differences between QPV and manual tracking are explained by the difference in effective size of particles tracked by QPV. Overall, these data indicate that automated tracking of the motion of cellular mass from QPI data can effectively be used to characterize effective diffusivity within living cells.

Fourier ptychographic microscopy (FPM) is a high-throughput computational imaging technology that enables wide-field and high-resolution imaging of samples with both amplitude and phase information. It holds great promise for quantitative phase imaging (QPI) on a large population of cells in parallel. However, detector undersampling leads to spectrum aliasing, which may significantly degenerate the resolution, efficiency, and quality of QPI, especially when an objective lens with a high space-bandwidth product is used. Here, we introduce a diagonal illumination scheme for FPM to minimize spectrum aliasing, enabling high-resolution QPI under a limited detector sampling rate. By orienting the LED illumination diagonally relative to the detector plane, the non-aliased sampling frequency of the raw image under oblique illumination can be maximized. This illumination scheme, when integrated with a color camera, facilitates single-shot, high-throughput QPI, effectively overcoming spectrum aliasing and achieving incoherent diffraction-limited resolution. Theoretical analysis, simulations, and experiments on resolution target and live cells validate the effectiveness and the proposed illumination scheme, offering a potential guideline for designing an FPM platform for high-speed QPI under the limited detector sampling rates.

The design of the illumination pattern is crucial for improving imaging quality of ghost imaging (GI). The S-matrix is an ideal binary matrix for use in GI with non-visible light and other particles since there are no uniformly configurable beam-shaping modulators in these GI regimes. However, unlike widely researched GI with visible light, there is relatively little research on the sampling rate and noise resistance of compressed GI based on the S-matrix. In this paper, we investigate the performance of compressed GI using the S-matrix as the illumination pattern (SCSGI) and propose a post-processing method called preconditioned S-matrix compressed GI (PSCSGI) to improve the imaging quality and data efficiency of SCSGI. Simulation and experimental results demonstrate that compared with SCSGI, PSCSGI can improve imaging quality in noisy conditions while utilizing only half the amount of data used in SCSGI. Furthermore, better reconstructed results can be obtained even when the sampling rate is as low as 5%. The proposed PSCSGI method is expected to advance the application of binary masks based on the S-matrix in GI.