Specular Components Research Articles

Polarized spectral bidirectional reflectance distribution function in visible band based on Cauchy’s empirical dispersion equation

The polarized bidirectional reflectance distribution function (pBRDF) can describe the changes between the Stokes vectors of incident and reflected light. The existing model can only describe the spatial distribution of the target’s polarization characteristics at a single wavelength, so further research is needed for the description of the target’s polarized spectral characteristics. In this paper, a modified three-component polarized spectral bidirectional reflectance distribution function (pSBRDF) is proposed, which combines Fresnel equation in the specular reflection component with Cauchy’s empirical dispersion equation, by introducing the wavelength variable and dispersion constants that do not change with wavelength. The degree of the linear polarization (DoLP) of two types of coated fabric samples was measured at three incident angles and 400 to 760 nm wavelength. The error of the model in describing the spectral and the spatial distribution of DoLP are controlled within 0.00743 and 0.0757 respectively, which proves the accuracy of the model. This research provides the model basis for analysis of the target’s polarization characteristics and the theoretical basis for the application of polarization detection.

Assessment of angular distribution of sound scattering in enclosures

This study proposes an approach for quantitatively assessing sound scattering degrees caused by objects within enclosures. It categorizes the high-frequency sound fields in rooms into two distinct components: (1) specular reflections arising from boundary surfaces, and (2) non-specular scattering contributed by objects (interiors). To achieve this, sound fields sampled on a sphere for two scenarios, with and without interiors, were decomposed into plane waves. The coherence between the impulse responses of these plane waves for these two scenarios is analyzed to obtain the proportion of specular and non-specular components within the room containing interiors. Derived from these coherence curves, the Equivalent Scattering Coefficients (ESCs) quantify the degree of scattering distributed across various directions, reflecting the interaction of sound waves with these interior elements. The extracted ESCs facilitate to quantification of the proportion of specular and non-specular components, which can be efficiently modeled separately and combined in a hybrid acoustic model, offering significant potential for sound field reconstruction.

Numerical modeling of acoustic scattering characteristic with wavenumber domain admittance

A conversion from the wavenumber domain acoustic reflection coefficient to the wavenumber domain acoustic admittance is formulated to deal with the acoustic reflection properties of arbitrary materials in numerical simulation. This method, which can represent arbitrary reflection directional properties, is an extended reactive boundary condition modelling method based on a spatial Fourier transform over the boundary surface. The advantages are that it is computationally inexpensive because it does not need to consider the interior of the material in the analysis, and that it can handle reflection characteristics obtained from actual measurements, etc. From the results of applying the wavenumber domain acoustic admittance to the numerical analysis, it has been confirmed that the proposed method can handle not only the specular reflection component, but also when arbitrary scattering components are included, or when the main reflection direction is changed from the specular reflection direction.

Fast high quality highlight removal using a simplified matrix iteration method

Recently, a global non-smooth optimization method was developed for efficiently eliminating specular highlights from single color image. Although this method was reported to be effective on both natural and medical images, its algorithm’s speed is slow due to the non-smoothness of the objective function. This paper proposes a global smooth optimization method, where two gradient regularization terms are used to describe diffuse and specular component features for texture details. A simplified optimality condition is established and thus a new iteration algorithm for specular highlight removal is proposed. By employing the gradient regularization of diffuse reflection, image texture detail can be preserved during specular highlight removal. Due to the smoothness of the objective function, the proposed smooth optimization algorithm has lower computational complexity and less storage requirement than the global non-smooth optimization algorithm. Furthermore, the proposed iteration algorithm is guaranteed to converge to a global optimal solution under a fixed step length. Experimental results demonstrate that the proposed smooth optimization algorithm is much faster than the non-smooth optimization algorithm. Moreover, the proposed highlight removal algorithm is more effective on benchmark natural images and real laparoscopic images than conventional highlight removal algorithms.

Laser biospeckle method for a fast and reliable microbioassay

Recently, the direct toxicity assessment (DTA) approach or bioassay has attracted much attention, as it can comprehensively evaluate water toxicity without examining a specific/individual chemical component. Bioassays are used to investigate how organisms respond to pollutants compared to controls. In this technique, a microscopic observation is required to know the critical features such as alive/dead, and swimming ability of microorganisms. As the size of the microorganism becomes smaller, observation becomes more difficult due to the narrower focal depth of the imaging system. In our study, to overcome the difficulties, we propose, to our knowledge, a novel technique for the microbioassay utilizing a biospeckle in the diffraction field generated from its movement. We employed Paramecia caudatum sized around 200–300 µm. The sample cell containing Paramecia was illuminated with a laser light with a diameter 15 mm and wavelength 635 nm. The specular component of the transmitted light was filtered out using a spatial filter placed at the Fourier plane and the biospeckle patterns in the diffraction field were acquired using a CCD camera as a movie. It is obvious that the dynamic properties of the biospeckle precisely reflects the movement of the scattering particles or Paramecia. Paramecia were exposed to HCl solutions with pH7.1, control, to 3.7 where all were dead. The swimming abilities of the Paramecia were successfully evaluated based on the crosscorrelation function of the frames of biospeckle patterns. The advantage of the method is that, owing to the non-imaging system, an enormous number of Paramecia can be processed as a whole, and a statistically significant estimation of the swimming ability of Paramecia under the influence of environmental pollution can be derived immediately.

Comparison of Simulation Methods for Glare Risk Assessment with Roller Shades

Daylight discomfort glare evaluation is important when selecting shading properties. New standards recommend allowable glare frequency limits but do not specify the modeling accuracy required for annual glare risk assessment. Fast simulation tools allow users to perform hourly glare evaluations within minutes. However, reliable evaluation of glare through roller shades requires accurate modeling of their specular and diffuse transmission characteristics, affected by color, materials, and weaving technology. This study presents a systematic comparison between commonly used glare simulation methods against the “ground truth” Radiance ray-tracing tool rpict in terms of hourly daylight glare probability (DGP), hourly vertical illuminance (Ev), and annual visual discomfort frequency. The results are presented for two shade fabrics using light transmission models with and without a peak extraction algorithm (Radiance–aBSDF and Radiance–BSDF) for the specular component. The impact of sky/sun discretization on glare prediction is also discussed. The results show that the Radiance 5–Phase Method (5PM) is superior when modeling direct sunlight and DGP through shades, while other investigated methods (3–Phase Method, imageless DGP, ClimateStudio Annual Glare) are not as robust for that purpose. Users are encouraged to understand the underlying assumptions in the imageless methods to avoid errors when simulating glare, especially due to the contrast effects.

S-LIGHT: Synthetic Dataset for the Separation of Diffuse and Specular Reflection Images.

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a specular-light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the multi-scale normalized cross correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

Computational ghost imaging with adaptive intensity illumination for scenes featuring specular surfaces

Imaging a target scene with specular surfaces is a daunting challenge for both direct imaging and indirect computational imaging techniques. The intense specular reflection component during the measurement severely degrades the quality of the reconstructed image, resulting in a substantial loss of scene information. To address this issue, we propose a computational ghost imaging (CGI) method with adaptive intensity illumination. Capitalizing on the encoded imaging feature of CGI, this method enables effective imaging of target scenes with specular surfaces through two series of measurements, eliminating the necessity for additional optical components. Based on the position and intensity information of pixels in the specular regions from the first series of measurements, our method modulates the illumination patterns to weaken the intensity of the specular region in the second series of measurements. Simulation and experimental results demonstrate that the utilization of these modulated illumination patterns for target scene measurement effectively mitigates interference from the specular surface during imaging. Consequently, the reconstructed image is capable of presenting more detailed information about the target scene other than the specular regions. Our work introduces a novel approach for imaging target scenes with specular surfaces and broadens the scope of applications for CGI in reality.

Learning physically based material and lighting decompositions for face editing

Lighting is crucial for portrait photography, yet the complex interactions between the skin and incident light are expensive to model computationally in graphics and difficult to reconstruct analytically via computer vision. Alternatively, to allow fast and controllable reflectance and lighting editing, we developed a physically based decomposition through deep learned priors from path-traced portrait images. Previous approaches that used simplified material models or low-frequency or low-dynamic-range lighting struggled to model specular reflections or relight directly without intermediate decomposition. However, we estimate the surface normal, skin albedo and roughness, and high-frequency HDRI maps, and propose an architecture to estimate both diffuse and specular reflectance components. In our experiments, we show that this approach can represent the true appearance function more effectively than simpler baseline methods, leading to better generalization and higher-quality editing.

Specular gloss estimation by measuring the colorimetric data produced by a reflection measurement at 8° of incidence

This paper presents an experimental investigation into the estimation of specular gloss from the colorimetric data. The 28 samples were selected from the Natural Color System (NCS) gloss scale, which had different combinations of lightness and gloss levels. The samples’ spectral reflectance and colorimetric data Y and L* were measured by a d:8° geometry reflectance spectrophotometer in both SCE (Specular Component Excluded) and SCI (Specular Component Included) modes. Additionally, the specular gloss of the samples at three common angles 20◦, 60◦, and 85◦ was measured using a gloss meter. The correlation and relationship between DYSCI-SCE and DL*SCI-SCE and the specular gloss values measured for the samples at different angles were evaluated and analyzed with linear and second-polynomial regression functions. The results were validated with a different set of data acquired from 32 random solid-coated samples. The results showed the best fitting was achieved at 60◦ of gloss measurement with a second-polynomial function. As the specular gloss of DY decreased, like in a matt sample, the estimation error of specular gloss increased with a large error of over 10%.

Selecting roller shade optical properties for glare protection

This paper presents a revised method for choosing roller shade properties that can significantly reduce the risk of glare when closed. State-of-the-art daylight modeling is employed to compute direct and diffuse light transmission through shading fabrics using BSDF datasets with the 5 Phase Method plus a peak extraction algorithm for the specular component. The analysis is parameterized by properties listed by manufacturers: openness factor, visible transmittance, and visible reflectance. In this way, we provide recommendations for the upper bounds of properties based on annual discomfort frequency (annual time percentage when daylight Glare Probability <5.5%). We discuss the impact of Radiance-aBSDF and related uncertainties, and the comparison with glare control classes proposed in Standard EN 14501.

A novel statistics for the NWDP: An appropriate fading model for 5G/6G mmWave communications

SummaryThere are many aspects concerning a new generation of communication systems that most existing channel models cannot address. For instance, the positioning of the transmitter and receiver is such that a large number of specular components are observed in the receiver due to the use of small cells. The two‐wave with diffuse power (TWDP) distribution is a model for the fading channel when two specular waves with many scattering components are present. The primary issue with this distribution is that its principal statistics are approximated. In this paper, precise analytical expressions for the statistics of this distribution are proposed. The proposed expressions only contain one multivariate Fox's ‐function term instead of the earlier approximations that included several complex mathematical functions like Legendre and Laguerre. The second issue with TWDP is that this model includes no more than two specular components, which in many environments is insufficient. Therefore, its generalization, that is, N‐wave with diffuse power (NWDP), is required. This channel‐fading model contains N specular components and multiple scattering components. This paper also calculates exact expressions for this distribution's statistics. In addition, the bit error rate (BER) for coherent and noncoherent modulations is calculated with the NWDP distribution for fading channel.

Automatic Indoor Radio Map Construction and Localization via Multipath Fingerprint Extrapolation

For fingerprint-based localization, the time-consuming and labor-intensive construction of offline radio map is the bottleneck which hinders its large-scale implementation. In this paper, we propose a radio map extrapolation and localization algorithm by exploiting the angles and delays of specular multipath components. First, using the concept of virtual anchor nodes (VANs), we calculate the virtual transmitter (VT) of each multipath component according to angle and delay information measured at a known point. By estimating the positions of reflector with these VTs, the angles and delays of the uplink multipath components transmitted at other locations in the indoor environment are extrapolated. Then, a channel fingerprint composed of the extrapolated angles and delays is proposed to represent the channel response in the angle-delay domain, which is spatially unique and discriminative. Thus, the radio map constructed such can significantly reduce the labor and time costs. Lastly, a convolutional neural network (CNN) is applied for indoor localization. The performance of the proposed fingerprint extrapolation and localization method is validated through extensive simulations with a ray-tracing channel model, which exhibits promising localization performance for our proposed scheme with reduced construction costs.

Portable multiscale form measurement technique for structured specular surfaces based on phase measuring deflectometry

Propelled by the rapidly growing demand for function incorporation and performance improvement, various specular components with complex structured surfaces are broadly applied in numerous optical engineering arenas. Form accuracy of the structured surfaces directly impacts the functioning of the specular components. Because the scales of these structures and/or the importance of their functions are usually designed differently, the structures require different measurement demands in scale, lateral resolution, and accuracy. In this paper, a multiscale form measurement technique is proposed based on triple-sensor phase measuring deflectometry for measuring structured specular surfaces. The proposed technique contains two sub-phase measuring deflectometry(PMD)-systems. Each sub-system works as a single segmentation PMD (SPMD) system and is designed to have different measurement scales, lateral resolutions, and accuracies to meet the measurement demands of the targeted surfaces. Two imaging sensors in the proposed technique cover the measured full-scale surface. The specular surface is separated into several continuous segments through algorithms and the spatial relationship of the continuous segments is established based on absolute depth data calculated through the triangular relationship between the two imaging sensors. The third imaging sensor with a long working distance only captures the field of the small-scale structures and reconstructs the structures based on gradient data to improve the structures’ reconstruction resolution and accuracy. In order to make it suitable for portable and embedded measurement, a compact configuration is explored to reduce system volume. Data fusion techniques are also studied to combine the measurement data of the two sub-systems. Experimental results demonstrate the validity of a portable prototype developed based on the proposed technique by measuring a concave mirror with small-scale structures.

Hybrid glaucoma detection model based on reflection components separation from retinal fundus images

The diagnosis of diseases associated to the retina is significantly aided by retinal fundus images. However, when flash illumination is used during image acquisition, specularity reflection can occur on images. The retinal image processing applications are popular now days in diseases detection such as glaucoma, diabetic retinopathy, and cataract. Many modern disease detection algorithms suffer from performance accuracy limitation due to the creation of specularity reflection problem. This research proposes a hybrid model for screening of glaucoma which includes a preprocessing step to separate specular reflections from corrupted fundus images, a segmentation step using modified U-Net CNN, a feature extraction step, and an image classification step using support vector machine (SVM) with different kernels. Firstly, the diffuse and specular components are obtained using seven existing methods and apply a filter having high emphasis with a function called similar in each component. The best method, which provides highest quality images, is chosen among the seven compared methods and the output image is used in next steps for screening of glaucoma. The experimental results of the proposed model show that in preprocessing step, maximum improvement in terms of PSNR and SSIM are 37.97 dB and 0.961 respectively. For glaucoma detection experiment the results have the accuracy, sensitivity, and specificity of 91.83%, 96.39%, and 95.37% respectively and AUROC of 0.971.

Enhancement of protein detection on cultural heritage samples after SYPRO™ Ruby staining by optical microscopy and micro-FTIR spectroscopy

The paper investigates SYPRO™ Ruby staining in combination with external reflection micro-FTIR spectroscopy, for the detection of proteinaceous media in paint layers on cultural heritage, from unembedded micro-fragments and samples embedded in cross-sections. Combining FTIR spectroscopy with staining helped to verify that the FTIR mapping is accurate when performed by the integration of the main amide I and II bands, despite their naturally occurrent distortions due to the specular component and material absorption/surface properties. The research filled some gaps in the published literature on SYPRO™ Ruby interaction with different Cultural Heritage materials, including identifying drawbacks, e.g. swelling mechanisms in the sample after staining. The effects of the staining were investigated on different reference samples containing rabbit skin glue (proteinaceous), and samples from cultural heritage case studies undergoing technical examination as part of research projects, where identification of protein is an important aspect of understanding the sequence of complex multi-layers within a sample. Results showed that, when external reflection µ-FTIR is performed after the staining, the contribution from amide I and II, which occurs at higher wavenumbers than in transmission or attenuated total reflection, is more resolved and therefore easier to determine. When inorganic or organic compounds are present in the same layer, variation in the position of amide bands can occur. However, they can be used for chemical mapping using simple data-treatment strategies, as validated with the positive staining. This type of data processing gives a good estimation of the protein distribution in the layers, both in terms of morphology and thickness, on mock-up samples and cross-sections from real case studies.

Effect of thickness, translucency, and substrates on the masking ability of a polymer-infiltrated ceramic-network material.

The aim of this in vitro study is to evaluate the masking ability of polymer-infiltrated ceramic-network materials (PICN) with different translucencies and thicknesses on multiple types of substrates. Ceramic samples were prepared of VITA ENAMIC blocks in two different translucencies (2M2-T, 2M2-HT) in a thickness range of 0.5-2.5 mm (±0.05 mm). Layered specimens were obtained using composite substrates in nine shades and transparent try-in paste. Spectral reflectance of specimens was measured using a Konica Minolta CM-3720d spectrophotometer and D65 standard illumination. CIEDE2000 color difference (ΔE00 ) between two samples was evaluated using 50%:50% perceptibility and acceptability thresholds. Specular component of the reflection was examined with Specular Component Excluded (SCE) and Included (SCI) settings. Statistical evaluation was performed by linear regression analysis, Kruskal-Wallis test, and multiplicative effect analysis. An increase in thickness of 0.5 mm reduces ΔE00 of HT samples to 73.5%, of T samples to 60.5% (p < 0.0001). Five substrates with HT specimens, and three substrates with T specimens had significantly different results from average (p < 0.05). There is a significant difference between SCE and SCI data depending on the wavelength (p < 0.0001). Masking ability of PICN materials is influenced by the thickness and translucency of the ceramic, and by the substrate. Reflection of the examined PICN material is characterized by both diffuse and specular reflection. Although PICN materials have been available on the market for 10 years now, there is a lack of information regarding their masking ability. Acquiring in-depth data and thereby practical experience of the factors affecting the esthetics of PICN materials is essential for creating perfectly lifelike restorations.

18‐1: Combining Annulus and Variable Aperture Source Methods to Separate Specular, Haze and Lambertian Reflection Components of ePaper Displays

The annulus light source method separates specular and diffuse components of reflected glare from display surfaces. Combining it with the variable aperture source method delivers source‐size dependence. Measuring diagnostic reflection samples and ePaper with mirror‐like or scattering surfaces confirmed that the source‐size dependence of reflected glare comes from haze scatter.

Three Dimensional Shape Reconstruction via Polarization Imaging and Deep Learning

Deep-learning-based polarization 3D imaging techniques, which train networks in a data-driven manner, are capable of estimating a target’s surface normal distribution under passive lighting conditions. However, existing methods have limitations in restoring target texture details and accurately estimating surface normals. Information loss can occur in the fine-textured areas of the target during the reconstruction process, which can result in inaccurate normal estimation and reduce the overall reconstruction accuracy. The proposed method enables extraction of more comprehensive information, mitigates the loss of texture information during object reconstruction, enhances the accuracy of surface normal estimation, and facilitates more comprehensive and precise reconstruction of objects. The proposed networks optimize the polarization representation input by utilizing the Stokes-vector-based parameter, in addition to separated specular and diffuse reflection components. This approach reduces the impact of background noise, extracts more relevant polarization features of the target, and provides more accurate cues for restoration of surface normals. Experiments are performed using both the DeepSfP dataset and newly collected data. The results show that the proposed model can provide more accurate surface normal estimates. Compared to the UNet architecture-based method, the mean angular error is reduced by 19%, calculation time is reduced by 62%, and the model size is reduced by 11%.

The Fluctuating Two-Ray Fading Model With Independent Specular Components

We introduce and characterize the independent fluctuating two-ray (IFTR) fading model, a class of fading models consisting of two specular components which fluctuate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">independently</i> , plus a diffuse component modeled as a complex Gaussian random variable. The IFTR model complements the popular fluctuating two-ray (FTR) model, on which the specular components are fully correlated and fluctuate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">jointly</i> . The chief probability functions of the received SNR in IFTR fading, including the PDF, CDF and MGF, are expressed in closed-form, having a functional form similar to other state-of-the-art fading models. Then, the IFTR model is empirically validated using multiple channels measured in rather diverse scenarios, including line of sight (LOS) millimeter-wave, land mobile satellite (LMS) and underwater acoustic communication (UAC), showing a better fit than the original FTR model and other models previously used in these environments. Additionally, the performance of wireless communication systems operating under IFTR fading is evaluated in closed-form in two scenarios: ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) exact and asymptotic bit error rate for a family of coherent modulations; and ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) exact and asymptotic outage probability.