Analysis utilizing a standard CIELUV metric and a cone-contrast metric custom-designed for different types of color vision deficiencies (CVDs) reveals that the discrimination thresholds for natural daylight do not vary between normal trichromats and individuals with CVDs, including dichromats and anomalous trichromats. Nevertheless, there are observable differences in thresholds when considering atypical light sources. This finding builds upon a prior report detailing the ability of dichromats to discern variations in illumination, specifically in simulated daylight shifts within images. Through the lens of the cone-contrast metric, we contrast daylight threshold shifts for bluer/yellower and unnatural red/green changes, suggesting a weak maintenance of sensitivity to daylight changes in X-linked CVDs.

The study of underwater wireless optical communication systems (UWOCSs) now investigates vortex X-waves, considering the coupling effects of orbital angular momentum (OAM) and spatiotemporal invariance. The correlation function and Rytov approximation provide the means to determine both the OAM probability density for vortex X-waves and the channel capacity of the UWOCS. Subsequently, a meticulous investigation into OAM detection probability and channel capacity is executed for vortex X-waves that transport OAM within anisotropic von Kármán oceanic turbulence. Elevated OAM quantum numbers produce a hollow X-configuration in the plane of reception. The energy of the vortex X-waves is implanted into the lobes, diminishing the likelihood of the vortex X-waves arriving at the receiving end. An increment in the Bessel cone angle causes a gradual centralization of energy, and consequently, the vortex X-waves become more localized. The development of UWOCS for bulk data transfer, utilizing OAM encoding, may be spurred by our research.

To achieve colorimetric characterization for the camera with an expansive color gamut, we propose employing a multilayer artificial neural network (ML-ANN), trained using the error-backpropagation algorithm, to model the color transformation from the camera's RGB space to the CIEXYZ standard's XYZ space. The ML-ANN's architecture, forward calculation process, error backpropagation method, and training strategy are detailed in this paper. The spectral reflectance curves of ColorChecker-SG blocks, combined with the spectral sensitivity curves of typical RGB camera channels, informed the development of a method for creating wide-color-gamut samples for the training and evaluation of ML-ANN models. The least-squares method was used, alongside various polynomial transformations, in a comparative experiment which took place during this period. The experimental data indicate that escalating the number of hidden layers and the number of neurons in each layer corresponds with a substantial diminishing of both training and testing error rates. The ML-ANN with optimal hidden layers has exhibited a decrease in mean training error and mean testing error, to 0.69 and 0.84 (CIELAB color difference), respectively. This performance significantly surpasses all polynomial transforms, including the quartic polynomial transform.

The investigation explores the development of the state of polarization (SoP) within a twisted vector optical field (TVOF) encompassing an astigmatic phase component, passing through a strongly nonlocal nonlinear medium (SNNM). The twisted scalar optical field (TSOF) and TVOF's propagation in the SNNM, influenced by an astigmatic phase, shows a reciprocating pattern of expansion and contraction, accompanied by the conversion from a circular to a filamentous beam distribution. Avacopan in vivo If the beams exhibit anisotropy, the TSOF and TVOF will rotate about the propagation axis. Propagation within the TVOF manifests reciprocal conversions between linear and circular polarizations, which are highly reliant on the starting power values, twisting strength parameters, and the initial beam designs. In a SNNM, the numerical results provide corroboration for the moment method's analytical predictions on the dynamic behavior of TSOF and TVOF during their propagation. The polarization evolution of a TVOF, within the context of a SNNM, is examined in detail from a physics perspective.

Information on object shapes, as demonstrated by previous studies, is vital for the accurate assessment of translucency. This study probes the connection between surface gloss and the perceptual experience of semi-opaque objects. The specular roughness, specular amplitude, and the light source's simulated direction were altered to illuminate the globally convex, bumpy object. As specular roughness was elevated, the perceived lightness and roughness of the surface also heightened. Despite the observable decrease in perceived saturation, the declines were considerably less significant when paired with increases in specular roughness. The analysis found an inverse correlation between perceived gloss and lightness, between perceived transmittance and perceived saturation, and between perceived roughness and perceived gloss, respectively. A positive correlation was noted in the relationship between perceived transmittance and glossiness, and also between perceived roughness and perceived lightness. Beyond perceived gloss, the impact of specular reflections extends to the perception of transmittance and color characteristics, as indicated by these findings. A follow-up analysis of image data demonstrated that perceived saturation and lightness could be explained by the reliance on different image regions that have varying chroma and lightness, respectively. In our research, we noted a systematic influence of lighting direction on the perception of transmittance, implying intricate perceptual interactions that merit further scrutiny.

The importance of phase gradient measurement in quantitative phase microscopy cannot be overstated for the study of biological cell morphology. This paper introduces a deep learning technique for direct phase gradient estimation, thereby avoiding the complexities of phase unwrapping and numerical differentiation. Numerical simulations under severe noise illustrate the robust performance of the proposed method. Finally, we demonstrate the method's applicability for imaging diverse biological cells with a diffraction phase microscopy setup.

Extensive efforts in both academic and industrial contexts have contributed to the development of numerous statistical and machine learning-based techniques for illuminant estimation. Undeniably challenging for smartphone cameras, single-color (i.e., pure color) images have, nonetheless, received limited consideration. The development of the PolyU Pure Color dataset, containing solely pure color images, was undertaken in this study. A compact multilayer perceptron (MLP) neural network, named 'Pure Color Constancy' (PCC), was also developed to assess the illumination of pure color pictures. This network relies on four colorimetric features extracted from the image: the chromaticities of the maximum, average, brightest, and minimum pixels. For pure color images in the PolyU Pure Color dataset, the proposed PCC method significantly surpassed the performance of competing learning-based methods. Across two other image datasets, its performance was comparable and displayed consistent performance across different sensors. An impressive performance was attained using a significantly smaller parameter count (approximately 400) and a remarkably brief processing time (around 0.025 milliseconds) for an image, all executed with an unoptimized Python package. For practical deployments, this proposed method proves an adequate solution.

Adequate visual distinction between the road and its markings is crucial for both safe and comfortable driving. Optimized road lighting designs, featuring luminaires with specialized luminous intensity distributions, will yield an improved contrast by capitalizing on the (retro)reflective characteristics of the road surface and markings. Given the limited understanding of road markings' (retro)reflective properties for incident and viewing angles crucial to streetlight design, the bidirectional reflectance distribution function (BRDF) values of selected retroreflective materials are measured over a wide range of illumination and viewing angles with a luminance camera in a commercial, close-proximity goniophotometer configuration. The RetroPhong model, newly optimized, successfully correlates with the experimental data, producing a good fit (root mean squared error (RMSE) = 0.8). The RetroPhong model's benchmarking against similar retroreflective BRDF models showcases its suitability for the current set of samples and measurement protocol.

Classical and quantum optics alike necessitate a component that embodies both wavelength beam splitting and power beam splitting capabilities. A triple-band, large-spatial-separation beam splitter operating at visible wavelengths is proposed, utilizing a phase-gradient metasurface in both x- and y-directions. The blue light, subject to x-polarized normal incidence, is split into two equal-intensity beams along the y-axis due to resonance within an individual meta-atom; the green light, similarly subjected to the same incidence, splits into two beams of identical intensity in the x-direction because of the varying sizes between adjacent meta-atoms; and the red light maintains its path uninterrupted without splitting. Optimization of the meta-atoms' size was achieved by considering their phase response and transmittance. At a normal angle of incidence, the simulated working efficiencies for wavelengths of 420 nm, 530 nm, and 730 nm are 681%, 850%, and 819%, respectively. Avacopan in vivo Furthermore, the sensitivities exhibited by oblique incidence and polarization angle are detailed.

Compensating for anisoplanatism in wide-field imaging through atmospheric media generally calls for a tomographic reconstruction of the turbulent volume. Avacopan in vivo The reconstruction process relies upon an estimate of turbulence volume, structured as a profile of thin, homogeneous strata. A layer's signal-to-noise ratio (SNR), a parameter that reflects the difficulty of detecting a homogeneous turbulent layer through wavefront slope measurements, is presented.