Using a standard CIELUV metric and a cone-contrast metric developed for distinct types of color vision deficiencies (CVDs), our results indicate that discrimination thresholds for changes in daylight do not differ between normal trichromats and individuals with CVDs, such as dichromats and anomalous trichromats; however, significant differences in thresholds emerge under non-standard illuminations. Previous research documenting dichromats' capability to distinguish illumination changes in simulated daylight images is expanded upon by this outcome. 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.
Underwater wireless optical communication systems (UWOCSs) research now includes vortex X-waves, their coupling effects of orbital angular momentum (OAM) and spatiotemporal invariance, as significant considerations. 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. Beyond that, a rigorous examination of OAM detection probability and channel capacity is done on vortex X-waves that bear OAM in anisotropic von Kármán oceanic turbulence. The results demonstrate that a rise in the OAM quantum number brings about a hollow X structure in the receiving plane, where the energy of vortex X-waves is funneled into the lobes, lessening the probability of vortex X-waves being received. With an augmentation in the Bessel cone angle, energy progressively gathers around its central distribution point, and the vortex X-waves exhibit enhanced localization. Our research endeavors could pave the way for the construction of UWOCS, enabling large-scale data transmission utilizing OAM encoding.
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. This paper presents the architecture, forward calculation, error backpropagation, and training policy for the ML-ANN. Based on the spectral reflectivity of ColorChecker-SG color blocks and the spectral responsiveness of RGB camera channels, a method for generating wide-color-range samples, essential for ML-ANN training and assessment, was developed. Simultaneously, a comparative study was carried out, employing different polynomial transformations in conjunction with the least-squares approach. Substantial reductions in both training and testing errors are observed in the experimental results when increasing the number of hidden layers and neurons in each hidden layer. Significant reductions in mean training and testing errors have been observed in the ML-ANN with optimal hidden layers, yielding values of 0.69 and 0.84, respectively (CIELAB color difference). This improvement is substantial compared to every polynomial transformation, including the quartic.
The evolution of the state of polarization (SoP) in a twisted vector optical field (TVOF) with an embedded astigmatic phase, within a strongly nonlocal nonlinear medium (SNNM), forms the focus of this investigation. In the SNNM, the effect of an astigmatic phase on the propagation of twisted scalar optical field (TSOF) and TVOF is manifested in a cyclical alternation of elongation and shrinkage, together with a reciprocal change between the initial circular shape and a thread-like beam distribution. ALKBH5 inhibitor 1 molecular weight When anisotropic, the beams' TSOF and TVOF will rotate about the propagation axis. In the course of propagation within the TVOF, the interplay between linear and circular polarizations is reciprocal and is significantly impacted by the initial power levels, twisting strength coefficients, and the initial configurations of the beam. Numerical results validate the moment method's analytical predictions concerning the TSOF and TVOF dynamics observed during propagation in a SNNM. The detailed physics of polarization evolution in a TVOF system, situated within a SNNM environment, are scrutinized.
Earlier investigations have revealed a correlation between object shape and the perception of translucency. The perception of semi-opaque objects is scrutinized in this research, with a particular emphasis on variations in surface gloss. Modifications to specular roughness, specular amplitude, and the simulated direction of the light source were performed on the globally convex, bumpy object. Increased specular roughness resulted in heightened perceptions of lightness and surface texture. While observations indicated a decrease in perceived saturation, the extent of this reduction was considerably less pronounced with corresponding increases in specular roughness. An inverse correlation was discovered between perceived lightness and gloss, saturation and transmittance, and gloss and roughness. Perceived transmittance was positively correlated with glossiness, and perceived roughness was positively correlated with perceived lightness. The influence of specular reflections extends to the perception of transmittance and color attributes, not merely the perception of gloss, as suggested by these findings. In a subsequent analysis of the image data, we discovered that the perception of saturation and lightness could be accounted for by the dependence on different image areas exhibiting greater chroma and lesser lightness, respectively. The data demonstrated a systematic connection between lighting direction and perceived transmittance, signifying a complexity of perceptual relationships that necessitates additional investigation.
A significant aspect of quantitative phase microscopy, in the context of biological cell morphological studies, is the precise measurement of the phase gradient. We introduce a deep learning method in this paper to directly compute the phase gradient, dispensing with phase unwrapping and numerical differentiation. The proposed method's robustness is evidenced through numerical simulations, which included highly noisy conditions. Additionally, we exhibit the method's utility in imaging various biological cells with a diffraction phase microscopy arrangement.
A variety of statistical and learning-based methods for illuminant estimation have emerged as a consequence of significant efforts in both academia and the industry. Pure color images, though not easily handled by smartphone cameras, have been surprisingly neglected. Within this investigation, the PolyU Pure Color image dataset was developed, featuring only pure colors. For estimating the illuminant in pure-color images, a lightweight multilayer perceptron (MLP) neural network model, labeled 'Pure Color Constancy' (PCC), was also created. Four color features were employed: the chromaticities of the maximum, average, brightest, and darkest image pixels. The proposed PCC method, when tested on the PolyU Pure Color dataset, displayed a significantly superior performance metric for pure color images compared to other leading learning-based methods. Results on the two other datasets indicated comparable performance, with a noteworthy demonstration of good cross-sensor performance. The image achieved excellent performance metrics with an unusually small parameter set (around 400) and a remarkably quick processing time (approximately 0.025 milliseconds), despite being processed using an unoptimized Python library. The proposed method's viability for practical deployments is assured.
To navigate safely and comfortably, there needs to be a noticeable variation in appearance between the road and its markings. Road surface and marking reflectivity can be better exploited with optimized road lighting designs utilizing luminaires with dedicated luminous intensity distributions to improve this contrast. Concerning the (retro)reflective properties of road markings under the incident and viewing angles significant for street lighting, only scant information is available. Therefore, the bidirectional reflectance distribution function (BRDF) values of certain retroreflective materials are quantified for a wide range of illumination and viewing angles employing a luminance camera in a commercial near-field goniophotometer setup. An optimized RetroPhong model demonstrates excellent agreement with the experimental data; the root mean squared error (RMSE) is 0.8. When evaluated alongside other relevant retroreflective BRDF models, the RetroPhong model yields the best results for the current specimens and measurement conditions.
Both classical and quantum optics require a device capable of functioning as both a wavelength beam splitter and a power beam splitter. We propose a visible-wavelength triple-band large-spatial-separation beam splitter employing a phase-gradient metasurface in both the x and y dimensions. Under x-polarized normal incidence, the blue light experiences a splitting into two beams of equivalent intensity, directed along the y-axis, attributable to resonance within an individual meta-atom. The green light, in contrast, splits into two beams of equal intensity, oriented along the x-axis, caused by variations in size between adjacent meta-atoms. Red light, however, passes without any splitting. Based on their phase response and transmittance, the size of the meta-atoms underwent optimization. Under normal conditions of incidence, the simulated working efficiencies at 420 nm, 530 nm, and 730 nm are 681%, 850%, and 819%, respectively. ALKBH5 inhibitor 1 molecular weight A discussion of the sensitivities associated with oblique incidence and polarization angle is also provided.
The correction of wide-field images in atmospheric systems, particularly to account for anisoplanatism, often involves the tomographic reconstruction of the turbulent air volume. ALKBH5 inhibitor 1 molecular weight Reconstruction hinges on the calculation of turbulence volume, represented as a series of thin, homogeneous layers. 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.