Surface Reflectance Characteristics Research Articles

Parameter Optimization Method for Metal Surface pBRDF Model Based on Improved Strawberry Algorithm

To study the polarization reflection characteristics of metal surfaces, a parameter optimization method for the polarization bidirectional reflection distribution function (pBRDF) model of metal surfaces based on the improved strawberry algorithm has been proposed. Firstly, the light scattering characteristics of metal surfaces were analyzed and a multi-parameter pBRDF model was constructed. Then, the working mechanism of the strawberry optimization algorithm was investigated and improved by introducing the chaotic mapping and Levy flight strategy to overcome the shortcomings, such as low convergence rate and easily falling into local optimum. Finally, the method proposed in this paper was validated by simulating open-source data from references and the obtained ones with a self-built experimental platform. The results show that the proposed method outperforms those by nonlinear least squares, particle swarm optimization and the original strawberry algorithm in fitting the detected degree of polarization (DOP) data, indicating the modeling accuracy was significantly improved and better suited to characterize the polarized reflection properties of metal surfaces.

An asymmetric road lighting concept: Probeam

An asymmetric road lighting concept known as Probeam is investigated in this study for energy efficiency, contrast and visibility of vertical objects and road markings in highway lighting. Calculations based on road lighting standards, road surface and markings reflection characteristics and typical Dutch highway geometry, reveal that Probeam lighting improves the average visibility of objects and road markings over symmetrical lighting, however, with a 14% increase in luminous flux as per current road lighting standards. This increase in luminous flux is attributed to the symmetrical lighting’s advantage in specular road surface reflection, leading to a reduction in the Counterbeam lobe size in the light intensity distribution when designed to meet the current road luminance requirement. Notably, by designing the Probeam luminaire to match symmetrical lighting’s average visibility of vertical objects, for removing the road luminance requirement and dimming the luminaire, energy consumption is reduced by 52%. Halving the Probeam luminaire’s mounting height leads to an impressive 82% energy savings. The study highlights the possibility of a balance in energy use and road safety using the Probeam concept, considering advancements in road luminaires and retroreflective materials. Due to glare, the relevance of the proposed Probeam concept is restricted to one-directional traffic on highways.

Dakota skipper distribution model for North Dakota, South Dakota, and Minnesota aids conservation planning under changing climate scenarios

Species distribution models are useful conservation planning tools for at-risk species, especially if they are linked to planning efforts, conservation delivery, and a changing environment. The Dakota skipper (Hesperia dacotae) is an endemic butterfly of mixed and tallgrass prairie of the northern Great Plains that is listed as federally threatened in the United States and Canada. We modeled broad-scale habitat suitability for the Dakota skipper by relating occurrence observations collected via non-probabilistic population surveys and a stratified sample of pseudo-absences to environmental predictors using a machine learning approach (i.e. Random Forest classification model). Predictors were summarized at two local scales and one landscape scale to reflect a potential spatial hierarchy of settlement responses. We used recursive feature elimination to select the top 25 covariates from a suite of predictor variables related to climate, topography, vegetation cover, biomass, surface reflectance, disturbance history, and soil characteristics. The top model included six bioclimatic, one soil, and 18 local- and landscape-scale vegetation variables and indicated an association with undisturbed grasslands with higher perennial grass and forb cover and biomass. The model performed well, with kappa and AUC estimates of 0.92 and 0.99, respectively, for 20% of data withheld for validation. To understand how climate change might affect Dakota skipper distribution, we applied the model using future 30-year bioclimatic predictions. Predicted suitable habitat declined and the climate envelope associated with Dakota skipper occurrence shifted north into Canada. While it is unknown to what degree the bioclimatic relationships in the model are biologically meaningful or are simply correlative with our non-probabilistic sample of occurrences, our results present an urgency to improve data collection for Dakota skipper populations and better understand climatic relationships, as climate change could have profound effects on populations and conservation planning. Regardless of climate or model uncertainty, our results demonstrate the importance of maintaining sufficient quantities and quality of grass on the landscape to support populations of Dakota skipper.

A Single-Frame Deflectometry Method for Online Inspection of Light-Transmitting Components.

Transparent materials are widely used in industrial applications, such as construction, transportation, and optics. However, the complex optical properties of these materials make it difficult to achieve precise surface form measurements, especially for bulk surface form inspection in industrial environments. Traditional structured light-based measurement methods often struggle with suboptimal signal-to-noise ratios, making them ineffective. Currently, there is a lack of efficient techniques for real-time inspection of such components. This paper proposes a single-frame measurement technique based on deflectometry for large-size transparent surfaces. It utilizes the reflective characteristics of the measured surface, making it independent of the surface's diffuse reflection properties. This fundamentally solves the issues associated with signal-to-noise ratios. By discretizing the phase map, it separates the multiple surface reflection characteristics of transparent devices, enabling transparent device measurement. To meet the requirements of industrial dynamic measurement, this technique only needs a simple and low-cost system structure, which contains just two cameras for image capture. It does not require phase shifting to complete the measurement, making it independent of the screen and having the potential for larger surface measurement. The proposed method was used to measure a 400mm aperture automobile glass, and the results showed that it is able to achieve a measurement accuracy on the order of 10 μ m. The method proposed in this paper overcomes the influence of surface reflection on transparent objects and significantly improves the efficiency and accuracy of large-sized transparent surface measurements by using a single-frame image measurement. Moreover, this method shows promise for broader applications, including measurements of lenses and HUD (Heads-Up Display) components, showcasing significant potential for industrial applications.

Underwater Structured Light Stripe Center Extraction with Normalized Grayscale Gravity Method.

The non-uniform reflectance characteristics of object surfaces and underwater environment disturbances during underwater laser measurements can have a great impact on laser stripe center extraction. Therefore, we propose a normalized grayscale gravity method to address this problem. First, we build an underwater structured light dataset for different illuminations, turbidity levels, and reflective surfaces of the underwater object and compare several state-of-the-art semantic segmentation models, including Deeplabv3, Deeplabv3plus, MobilenetV3, Pspnet, and FCNnet. Based on our comparison, we recommend PSPnet for the specific task of underwater structured light stripe segmentation. Second, in order to accurately extract the centerline of the extracted light stripe, the gray level values are normalized to eliminate the influence of noise and light stripe edge information on the centroids, and the weights of the cross-sectional extremes are increased to increase the function convergence for better robustness. Finally, the subpixel-structured light center points of the image are obtained by bilinear interpolation to improve the image resolution and extraction accuracy. The experimental results show that the proposed method can effectively eliminate noise interference while exhibiting good robustness and self-adaptability.

BRDF representation in response to the build orientation in 3D-printed digital materials

Additively manufactured (AM) parts still lack a thorough understanding of their optical properties, particularly surface texture and reflectance characteristics at different viewing angles. This study examines the reflectance properties of material jetting (MJT) parts using bidirectional reflectance distribution functions (BRDFs). The visual appearance of the MJT parts was analyzed using a gonio-spectrophotometer at 328 unique incidence and viewing geometries for seven different wedge angles for build orientation (BO) from 0° to 90° at 15° intervals. The redundancy analysis (RDA) and principal component analysis (PCA) were used to study BO and to determine the prominent measurement geometries. The results indicate higher BOs resulted in more color and texture variation and rougher surfaces, with Sq 4.21 μm vertical compared to 1.42 μm for horizontal BOs. Furthermore, it affected the visual representation and parametric estimation of BRDF, where significantly lower luminance, more diffuse reflection, and less hue distribution were observed for all CMYK resins printed at higher BOs. Accordingly, vertically printed surfaces showed a wider near-to-specular luminance area than other BOs. An analysis of the bidirectional reflectance property suggests that a gonio-spectrophotometer can be embedded in the printing process and quality assurance in AM as a computationally efficient model.

Study of silicone hydrogel contact lenses’ surface reflection characteristics using confocal microscopy

The physical and chemical properties of contact lenses (CLs) differ significantly from one another. This is already covered by the FDA classification, which divides soft lenses into groups and subgroups for additional characteristics. The differences relate to both the interior and surface of the lens. Several differences in the surface characteristics of individual contact lenses have been studied and demonstrated to date. However, one of their fundamental physical properties, that is light reflection or, quantitatively, reflectance has not been compared. This paper describes the surface differences of a range of silicone-hydrogel (SiHy) lenses using reflectance confocal microscopy. It shows the relationship between the amount of light reflected from the lens surface and the material parameters. Common SiHy lens materials were used in the study, including two lenses with surface modifications. Light incident at the interface between two media (phosphate-buffered saline and lens) with different refractive indices is partially reflected. The normalized results show significant differences between the reflection signals (1 vs 0.07), and that they are not correlated with the refractive index (R2 = 0.5536). For the water content (%H2O), a general trend was observed that the higher the %H2O, the lower the reflection signal is (R2 = 0.8105). The reflection signal and surface modulus show the best correlation. (R2 = 0.9883). The proposed CLs analysis method, using reflectance confocal microscopy, provides data to differentiate between lenses with and without surface modifications.

3D Reconstruction Method of Carbon Fiber Reinforced Plastics Components Based on Pre-calibration Measurement Pose

According to the surface reflection characteristics of carbon fiber reinforced plastics and the geometric characteristics of aircraft panel parts, a robot automatic measurement system based on line laser scanning is designed. The selection criteria of measurement pose and the pre-calibration method of measurement pose based on a laser tracker are given. A 3D reconstruction method of global stitching of large-scale parts based on pre-calibration measurement pose is proposed, Finally, the correctness and effectiveness of the proposed method are verified by measuring typical samples with a prototype system.

Research of the Luminance of Asphalt Pavements in Trafficked Areas

A key factor for safe and comfortable driving on roads are properly reflective and well visible pavement surfaces at night. The brightness of the road pavement surface depends on the amount of light falling on it and the reflection properties of the road pavement surface at any point. The luminance of the pavement depends on its physical condition, age and type of pavement, direction of illumination, and observation conditions. Different pavements can have different reflection characteristics that depend on the surface texture, materials, and binder (type and quantity). Experimental research was carried out on the carriageways and bicycle paths of Vilnius city streets, which differ in color and age. The analysis of the research results showed differences between the surface reflectance characteristics of these pavements depending on the color of the pavement, surface conditions, and age. The reflection properties of red asphalt pavements are better than black ones when the pavement surface is wet or moist. The reduced luminance coefficients of the carriageway (asphalt pavement installed in 2021) are about 12% lower than those of the carriageway pavement installed 10 years ago and about 60% lower for wet and moist pavements. The results obtained from the research are significant for street designers when choosing the type of pavement and designing street lighting.

Machine learning based combinatorial analysis for land use and land cover assessment in Kyiv City (Ukraine)

The main goal of this study is to evaluate different models for further improvement of the accuracy of land use and land cover (LULC) classification on Google Earth Engine using random forest (RF) and support vector machine (SVM) learning algorithms. Ten indices, namely normalized difference vegetation index, normalized difference soil index, index-based built-up index, biophysical composition index, built-up area extraction index (BAEI), urban index, new built-up index, band ratio for built-up area, bare soil index, and normalized built up area index, were used as input parameters for the machine learning algorithms to improve classification accuracy. The combinatorial analysis of the Sentinel-2 bands and the aforementioned indices allowed us to create four combinations based on surface reflectance characteristics. The study includes data from April 2020 to September 2021 and April 2022 to June 2022. The multitemporal Sentinel-2 data with spatial resolutions of 10 m were used to determine the LULC classification. The major land use classes such as water, forest, grassland, urban areas, and other lands were obtained. Generally, the RF algorithm showed higher accuracy than the SVM. The overall accuracy for RF and SVM was 86.56% and 84.48%, respectively, and the mean Kappa was 0.82 and 0.79, respectively. Using the combination 2 with the RF algorithm and combination 4 with the SVM algorithm for LULC classification was more accurate. The additional use of vegetation indices allowed to increase in the accuracy of LULC classification and separate classes with similar reflection spectra.

Polarization reflection distribution characteristics of wakes on the sea surface.

Research on the polarization reflection distribution characteristics of wakes on the sea surface can provide a theoretical basis for ocean wake target detection and has important research value in the field of ship and underwater moving target monitoring. The Kelvin wake model and the Cox-Munk model are used to describe a wake on a rough sea surface. Considering the atmospheric Rayleigh scattering and the reflection characteristics of a rough sea surface, a visible spectrum band wake polarization characteristic model based on the Stokes vector and Mueller matrix is established to explore the polarization reflection distribution characteristics of wakes on the sea surface under skylight background at different wind speeds, wind directions, and sun angles. A simulation is done of the airborne polarization reflection imaging of wakes on a rough sea surface. The results show that under the determined observation angle, the polarization distribution characteristics of wakes on a rough sea surface are mainly related to the angle of the sun. The polarization contrast of simulated wakes in typical scenes is acceptable, and it is feasible to detect sea wake targets by the polarization method. The analysis and simulation of the wake polarization characteristics model can provide a theoretical basis for ocean wake target detection.

Research on the detection probability curve characteristics of long-range target based on SPAD array lidar

Using single photon avalanche diode (SPAD) array lidar to detect long-range target, the difference of target surface characteristics will cause the distortion of the detection probability curve. This distortion severely limits the ability of target feature extraction and recognition. In this paper, a detection probability model for detecting long-range target using SPAD array lidar is established, which considers the influence of the difference of target surface structural characteristics (distance and pose) and reflection characteristics (reflectivity and cross-sectional area). Based on the finite element analysis method, the proposed model can calculate the detection probability when the target surface has the above characteristics difference. The full width at half maximum (FWHM) and skewness are used to evaluate the distortion of the detection probability curve. It reveals that with the increase of the structural characteristic difference of the target, the increasing trend of FWHM satisfies the cubic polynomial, while the decreasing trend of skewness satisfies the cubic polynomial. As the ratio of the reflection characteristic of the target increases, the decreasing trend of FWHM satisfies the first-order polynomial, while the increasing trend of skewness satisfies the first-order polynomial. The experimental results show that the feature vector composed of the detection probability curve features (FWHM, skewness, and total detection probability) can be used to identify the pixels containing target surfaces with different distances. And the identifiable distance difference is less than the system pulse width distance. This paper lays a theoretical foundation for target characteristic analysis and target recognition based on SPAD array lidar.

Vegetation and land classification method based on the background noise rate of a photon-counting LiDAR.

The changing of vegetation is a sensitive signature of global warming, and satellite photon-counting laser altimeters provide an effective way to monitor the changing of vegetation. Based on the background noise difference between vegetation-covered areas and bare lands, we proposed a classification method to distinguish vegetation-covered areas from the raw photons measured by photon-counting laser altimeters in relatively flat areas. First, a theoretical noise model was established considering the influence of the sunlight incident direction and reflection characteristics of different surfaces. Second, the thresholds from the proposed theoretical model were calculated and tested to classify the along-track land-cover types for the Ice, Cloud, and Elevation Satellite-2 (ICESat-2) photon-counting laser altimeter. Then, the study areas near Seattle and Romania in summer were selected and the classification method was verified to achieve an overall accuracy of over 77% (the strong beam) and over 76% (the weak beam) for both thresholds and areas. Our method utilized the noise photons with vegetation canopy reflection information, which are enormous in quantity and easy to extract compared to the signal photons. More importantly, this method reduces the requirements of the optical images (that are used as prior knowledge). The results show that using the noise photons of the weak beam may be more potential for the classification of vegetation and land than using the signal photons of the weak beam. We extended the research on the mechanism and application of ICESat-2 in forestry.

Model-data comparison of sound propagation in a glacierized fjord with a simulated brash ice surface.

Glacier ice loss impacts sound propagation within Arctic fjords. Regular calving events contribute to a collection of floating ice fragments, known as brash ice, at the ocean surface that obstruct the natural and anthropogenic acoustic signals, yet are difficult to characterize. Transmission loss measurements using a maximum length sequence (m-sequence) signal were conducted in September 2017 near Hansbreen glacier in Hornsund Fjord, Svalbard with dense brash ice present at the water surface. An acoustic model of the brash ice surface was inferred through consideration of the experimental geometry, arrival amplitude, and travel time difference between the direct and surface reflected arrivals from the source to two receivers. The inferred surface was then incorporated into a forward simulation of the environment using sound speed profiles measured during the experiment. BELLHOP ([Porter and Bucker (1987). J. Acoust. Soc. Am. 82(4), 1349-1359],), a ray tracing code available in the Acoustics Toolbox (HLS Inc., San Diego, CA), was used to track the time difference of arrivals and amplitudes of the modeled direct and surface reflected rays. Comparisons between the measured and simulated results provide insight into the geometric shape and reflection characteristics of the brash ice surface within this and similar environments.

A Coupled BRDF CO2 Retrieval Method for the GF-5 GMI and Improvements in the Correction of Atmospheric Scattering

The Greenhouse Gases Monitoring Instrument (GMI), on board the Chinese Gaofen-5 (GF-5) satellite, provides rich observation data for the global remote sensing of atmospheric CO2. To meet the high-precision satellite retrieval needs of atmospheric CO2, this paper designs a coupled bidirectional reflectance distribution function (BRDF) CO2 retrieval (CBCR) method, which describes the surface reflectance characteristics by the BRDF, corrects for atmospheric scattering based on full physics retrieval theory, and ensures the stable retrieval of multiple parameters and atmospheric CO2 by enriching prior constraints. Theoretical analysis shows that the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics is significantly related to the aerosol optical depth (AOD), solar zenith angle (SZA), and viewing zenith angle (VZA). The validation of GMI CO2 retrievals shows that the CBCR method significantly reduced the influence of the surface bidirectional reflectance characteristics under high AOD and high SZA conditions, decreased the atmospheric CO2 retrieval error from 0.58 ± 5.64 ppm to −1.33 ± 3.13 ppm, and increased the correlation with the temporal variation of actual atmospheric CO2 from 34.7 to 76.8%. Our CBCR method can correct the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics on atmospheric CO2 retrieval, and this work demonstrates that describing the surface reflectance characteristics by using BRDF is a promising idea in the field of satellite CO2 retrievals.

Measurement and modeling of reflection characteristics of hole inner surface based on endoscopic image

Reflection characteristic is the law of specular and diffuse reflection after receives light of the surface, usually expressed by the ratio of irradiance of incident direction to the emissivity of observation direction, namely bidirectional reflection distribution function (BRDF). A method to measure BRDF for hole inner surface based on the endoscope image and morphology is proposed, which established the relationship between BRDF and morphology. Taking stainless steel and galvanized internal threaded as an example, the axial images in the holes are collected, and the BRDF of internal surface is calculated through the image brightness and the normal direction. The distribution characteristics of BRDF on the inner surface of different materials are analyzed. Based on the Phong model, the inBRDF parameter model of the inner surface is established. Research shows that the inBRDF model is consistent with measured results, and the average fitting error of the two materials is only 6.22%. The inBRDF method of hole inner surface proposed in this paper has high measurement efficiency and strong universality of equipment, and it is preferred to be applied on hole inner surface quality detection accordingly.

The Map Data of BRDF-Adjusted Surface Reflectance from GOCI Geostationary Satellite Imagery over Korean Peninsula

In this study, the spatial maps of the BRDF (Bidirectional Reflectance Distribution Function) adjusted surface reflectance (SR) were estimated by using the Geostationary Ocean Color Imager (GOCI) mounted on the Communication, Ocean and Meteorological Satellite (COMS) over the Korean Peninsula. The BRDF-Adjusted surface Reflectance (BAR) is a more effective indicator that not only quantitatively identifies the growth characteristics of vegetation, but also corrects the bidirectional error in the time series observation characteristics, because the surface reflectance is changed according to the solar altitude during the daytime period. Therefore, this BAR products have high data utilization in various fields such as agriculture, environment, land surface information, and atmosphere. In this study, BRDF-adjusted surface reflectance maps were calculated for the Korean peninsula from April 2011 to December 2012 with hourly temporal resolution from 9 a.m. to 4 p.m. For the BAR surface reflectance, the spatial observation range is from latitude 34° N to 39 °N and longitude 125 ° E to 130 ° E, and the spatial resolution is 500 m. The semi-empirical BRDF model was used to calculate the BRDF-adjusted surface reflectance, and the radiometric characteristics of surface reflectance were decomposed into isotropic scattering, geometric scattering, and volumetric scattering. For this model simulation, at least 7 clear pixels are required to fit BRDF model. In this study, unlike the Nadir BRDF-Adjusted surface Reflectance (NBAR) calculation method which was calculated from the existing polar orbiting satellites, semi-empirical BRDF modeling was performed with a value fixed to the satellite viewing angle for each pixel since geostationary satellites of GOCI are difficult to observe in the nadir direction unlike polar satellites. It is more effective to perform BRDF correction by fixing them at the viewing angle in the case of GOCI geostationary satellite.

Assessing the quality of polished brittle optical crystal using quasi-Brewster angle technique

Polishing is a main process in achieving high-quality surfaces of optical components. However, effective assessing technique for rough stage in the polishing process is sparse so that hinders the study on the mechanism and optimization of polishing. In this study, we propose an inspection method for polishing quality based on quasi Brewster angle technology (qBAT). An equivalent medium layer theory and its model are developed to accurately describe the optical reflection characteristics of a rough surface. Hence both rough- and fine-polishing qualities can be evaluated by the qBAT approach. To demonstrate the newly proposed method, laser crystal, gadolinium gallium garnets, is studied by computational simulation and experiments. A high consistence is achieved between theoretical simulation and experimental results, which proves the robustness of the method to the rough surfaces. To our knowledge, it is the first time that the qBAT is developed to evaluate the polishing quality covering rough- and fine-polishing stages. This capability shows great potential in fundamental research and process optimization of polishing brittle-hard materials.

Back‐lobe mitigation of a compact DGS microstrip patch antenna using an artificial magnetic conductor surface

This work proposes a novel compact artificial magnetic conductor (AMC) surface backed microstrip antenna of dimension (0.29λ0 × 0.17λ0 × 0.015λ0) for improving the antenna radiation characteristics. The microstrip antenna considered here for performance improvement has a defected ground plane; thus, giving rise to undesired back-lobe radiation. Thanks to the, in-phase reflection characteristics of the AMC surface, gain improvement of more than 3 dBi has been achieved with a front-to-back lobe ratio improvement of 12 dB. This structure resonates at 5.8 GHz with an impedance bandwidth improvement of 13%. The overall antenna dimensions are (0.67λ0 × 0.8λ0 × 0.13λ0), where λ0 is the free space wavelength. To prove the concept, a physical prototype of the proposed antenna structure has been fabricated and the return loss, radiation pattern and gain have been verified. The obtained results are satisfactory and matching with the estimated results.

A Novel Algorithm for Leaf Incidence Angle Effect Correction of Hyperspectral LiDAR

As a novel remote sensor, hyperspectral LiDAR is faced with the incidence angle effect, which restricts its quantitative applications. However, the current radiometric correction algorithms have some limitations, concentrating on: 1) the mathematically polynomial fitting; 2) adjacent wavelength ratio such as ratio vegetation index; and 3) perfect Lambertian assumption and using the Lambert cosine law to correct the effect. In this study, a practical and proper correction algorithm is proposed to overcome these limitations. First, to better characterize the complex reflection characteristics of the object surface, a combination of the Lambert law and Beckmann law is applied to represent the object surface. Then, it considers the impact of both wavelength and incidence angle on describing the surface roughness factor and diffuse fraction. Finally, a modified and physically based radiometric correction algorithm is generated. It provides the detailed correction equations for intensity and reflectance data recorded by hyperspectral LiDAR. To obtain its parameters and verify its reliability, leaves (ten samples per species, 30 in total) were stochastically collected from three broadleaf trees to experiment. The results showed that the algorithm achieved good performances by comparing the intensity and reflectance changes before and after removing the leaf incidence angle effect. Since it is physically based, the algorithm could promisingly be a fundamental solution to eliminate the incidence angle effect for hyperspectral LiDAR.