Model of bidirectional reflectance distribution function for metallic materials

Based on the three-component assumption that the reflection is divided into specular reflection,directional diffuse reflection,and ideal diffuse reflection,a bidirectional reflectance distribution function（BRDF） model of metallic materials is presented.Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection,the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection.This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials.Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials.

Bidirectional reflectance one-dimensional rough distribution function modeling of surface in the microwave band

In this study, the bidirectional reflectance distribution function （BRDF） of a one-dimensional conducting rough surface and a dielectric rough surface are calculated with different frequencies and roughness values in the microwave band by using the method of moments, and the relationship between the bistatic scattering coefficient and the BRDF of a rough surface is expressed. From the theory of the parameters of the rough surface BRDF, the parameters of the BRDF are obtained using a genetic algorithm. The BRDF of a rough surface is calculated using the obtained parameter values. Further, the fitting values and theoretical calculations of the BRDF are compared, and the optimization results are in agreement with the theoretical calculation results. Finally, a reference for BRDF modeling of a Gaussian rough surface in the microwave band is provided by the proposed method.

Modeling three-dimensional forest structures to drive canopy radiative transfer simulations of bidirectional reflectance factor

Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.

Three-Component Model for Bidirectional Reflection Distribution Function of Thermal Coating Surfaces

We present a bidirectional reflection distribution function （BRDF） model for thermal coating surfaces based on a three-component reflection assumption, in which the specular reflection is given according to the microfacet theory and Snell＇s law, the multiple reflection is considered Nth cosine distributed, and the volume scattering is uniformly distributed in reflection angles according to the experimental results. This model describes the reflection characteristics of thermal coating surfaces more completely and reasonably. Simulation and measurement results of two thermal coating samples SR107 and S781 are given to validate that this three-component model significantly improves the modeling accuracy for thermal coating surfaces compared with the existing BRDF models.

Modeling bidirectional reflection distribution function of microscale random rough surfaces

The radiative properties of three different materials surfaces with one-dimensional microscale random roughness were obtained with the finite difference time domain method(FDTD) and near-to-far-field transformation.The surface height conforms to the Gaussian probability density function distribution.Various computational modeling issues that affect the accuracy of the predicted properties were discussed.The results show that,for perfect electric conductor(PEC) surfaces,as the surface roughness increases,the magnitude of the spike reduces and eventually the spike disappears,and also as the ratio of root mean square roughness to the surface correlation distance increases,the retroreflection becomes evident.The predicted values of FDTD solutions are in good agreement with the ray tracing and integral equation solutions.The overall trend of bidirectional reflection distribution function(BRDF) of PEC surfaces and silicon surfaces is the same,but the silicon's is much less than the former's.The BRDF difference from two polarization modes for the gold surfaces is little for smaller wavelength,but it is much larger for the longer wavelength and the FDTD simulation results agree well with the measured data.In terms of PEC surfaces,as the incident angle increases,the reflectivity becomes more specular.

Multi-factor Analysis of Reflection from Granite Surfaces

Many earlier experiments have shown that reflection from rock surfaces depends upon surface roughness,in-cidence zenith angle,viewing zenith angle,incidence azimuth and viewing azimuth. However,no research exists show-ing the interaction effects of these variables. Using granite as a model surface,we have designed an orthogonal,two level test having seven factors. Analysis of variance shows that surface roughness,relative viewing azimuth,and the in-teraction between these two factors are the largest sources of variance in our experiment. Hence we should include the interaction term in reflection models of granite.

Degree of polarization based on the three-component pBRDF model for metallic materials

An expression of degree of polarization（DOP） for metallic material is presented based on the three-component polarized bidirectional reflectance distribution function（p BRDF） model with considering specular reflection, directional diffuse reflection and ideal diffuse reflection. The three-component p BRDF model with a detailed reflection assumption is validated by comparing simulations with measurements. The DOP expression presented in this paper is related to surface roughness, which makes it more reasonable in physics. Test results for two metallic samples show that the DOP based on the three-component p BRDF model accords well with the measurement and the error of existing DOP expression is significantly reduced by introducing the diffuse reflection. It indicates that our DOP expression describes the polarized reflection properties of metallic surfaces more accurately.

Shape recovery using high dynamic range images

An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.

Comparative Study on Polarization Spectral Parameters of Fruit in Southern Xinjiang Based on Roujean Model

Based on the study of phase angle and wavelength in pBRDF (Polarized bidirectional reflectance distribution function), roujean model was proposed to describe Orient (Polarization phase angle) quantitatively. The Roujean model was used to quantitatively describe different fruits intensity components (F00) and polarization phase angle (Orient), and the simulation results were analyzed and compared using statistical analysis and comparison methods to realize the prediction from the regular model to the outdoor fruit tree canopy to the canopy of outdoor fruit tree canopy random distribution. The experimental results showed that: 1) when the phase angle of jujube was 52.19°, 66.51° and 88.26°, the R2 and average errors of F00 parameters described by Roujean model are 0.9982, 0.9963, 0.9912 and 3.80%, 4.17%, 6.40%, respectively; and the R2 and average error of Orient parameters described by Roujean model are 0.9056, 0.9223, 0.9260 and 6.23%, 3.32%, 8.05%, respectively;It can be seen that roujean model can quantitatively describe the Orient parameter of jujube;2) When the phase angle of apricot was 70.99°, 71.28° and 67.91°, the R2 and average errors of F00 parameters described by Roujean model is 0.9862, 0.9823, 0.9792 and 3.40%, 4.82%, 5.19%, respectively; And the R2 and average error of Orient parameters described by Roujean model are 0.9382, 0.8947, 0.8849 and 7.19%, 9.28%, 9.47%, respectively. Roujean model can also quantitatively describe the Orient parameter of white apricot. In summary, the Roujean model can provide a good quantitative description of f00 and a good quantitative description of Orient, which in turn can predict the pBRDF parameter for more fruits with different incidence and detection directions. It can correct the influence of angle factor in the nondestructive testing of outdoor fruits.

Visible characteristics of space-based targets based on bidirectional reflection distribution function

A precise modeling method of visible characteristics of the space-based target was presented based on bidirectional reflection distribution function (BRDF). The background characteristics of the space-based target were represented to build models of direct solar radiation and reflected radiation of the Earth based on blackbody radiation theory. The geometry characteristics of the target were analyzed to establish a surface equation of each surface based on its body coordinate system. The material characteristics of the target surface were described by introducing a BRDF model which considers the character of surface Gauss statistics and self-shadow and is obtained by measurement and modeling in advance. The relative positions of the space-based target, the background radiation sources and the observation platform were determined based on coordinate con- version to judge contributing surface of the target to observation system. Then a mathematical model on visible characteristics of the space target for the given optical system was built by summing reflection components of all the surfaces. Simulation of visible characteristics of the space-based target in orbit was achieved according to its given geometrical dimensions, physical parameters and orbital parameters. The results show that the method is effective for analysis on visible characteristics of the space-based target when single reflection is considered and its surface is regularly described in a surface equation, which provides a way to real-time calculation of visible characteristics of the space-based target.

A WDM-PON with DPSK modulated downstream and OOK modulated upstream signals based on symmetric 10 Gbit/s wavelength reused bidirectional reflective SOA

We investigate a wavelength-division-multiplexing passive optical network(WDM-PON) with centralized lightwave and direct detection. The system is demonstrated for symmetric 10 Gbit/s differential phase-shift keying(DPSK) downstream signals and on-off keying(OOK) upstream signals,respectively. A wavelength reused scheme is employed to carry the upstream data by using a reflective semiconductor optical amplifier(RSOA) as an intensity modulator at the optical network unit(ONU). The constant-intensity property of the DPSK modulation format can keep high extinction ratio(ER) of downstream signal and reduce the crosstalk to the upstream signal. The bit error rate(BER) performance of our scheme shows that the proposed 10 Gbit/s symmetric WDM-PON can achieve error free transmission over 25-km-long fiber transmission with low power penalty.

Winter wheat geometry identification by bidirectional canopy reflected spectrum

Effect of crop leaf angle on canopy reflected spectrum cannot be ignored in the inversion of leaf area index(LAI)and the monitoring of the crop growth condition using remote sensing technology.In this study,experiments on winter wheat(Triticum aestivum L.)were conducted to identify crop leaf angle distribution(LAD)by bidirectional canopy reflected spectrum.Canopy reflected spectrum has significant differences among erectophile,planophile and horizontal geometry varieties at essentially the same LAI value.Canopy reflectance value at near infrared of the erectophile variety was lower than that of the horizontal variety.The effects of LAI and crop LAD on canopy reflectance were studied among erectophile,planophile and horizontal LAD varieties.The Standard Deviation(STDEV)of canopy reflectance at the near infrared bands(800 nm and 1100 nm)was more significant than those of visible bands(450 nm,550 nm,680 nm).It indicates that near infrared bands could be used for different LAD wheat varieties identification.The method for identification of crop geometry parameters was by the bidirectional canopy reflectance at different wave bands and view angles.The bidirectional reflectance of visible and near infrared bands at 15°,30°and 45°field of view for the main viewing plane could be used for identification of erectophile,planophile and horizontal LAD varieties based on bidirectional data.For erectophile varieties,the bidirectional canopy reflectance at near infrared was f45°>f15°>f30°(f45°,f15°and f30°mean the canopy reflectance at 45°,15°,and 30°,respectively),in the visible band it was f45°>f15°≈f30°.For planophile varieties,the bidirectional canopy reflectance in the near infrared and visible band was f15°>f45°>f30°.For horizontal varieties,the bidirectional canopy reflectance in the near infrared and visible band was f45°>f30°>f15°.So,it is feasible to identify erectophile,planophile and horizontal varieties of wheat by bidirectional canopy reflected spectrum.

An attention-embedded GAN for SVBRDF recovery from a single image

Learning-based approaches have made substantial progress in capturing spatially-varying bidirectional reflectance distribution functions(SVBRDFs)from a single image with unknown lighting and geometry.However,most existing networks only consider per-pixel losses which limit their capability to recover local features such as smooth glossy regions.A few generative adversarial networks use multiple discriminators for different parameter maps,increasing network complexity.We present a novel end-to-end generative adversarial network(GAN)to recover appearance from a single picture of a nearly-flat surface lit by flash.We use a single unified adversarial framework for each parameter map.An attention module guides the network to focus on details of the maps.Furthermore,the SVBRDF map loss is combined to prevent paying excess attention to specular highlights.We demonstrate and evaluate our method on both public datasets and real data.Quantitative analysis and visual comparisons indicate that our method achieves better results than the state-of-the-art in most cases.

First Look of Surface Vegetation from the Advanced Geostationary Radiation Imager(AGRI) onboard Fengyun-4B

For many years, the status of surface vegetation has been monitored by using polar-orbiting satellite imagers such as Moderate Resolution Imaging Spectroradiometer(MODIS). However, limited availability of clear-sky samples makes the derived vegetation index dependent on multiple days of observations. High-frequency observations from the geostationary Fengyun(FY) satellites can significantly reduce the influence of clouds on the synthesis of terrestrial normalized difference vegetation index(NDVI). In this study, we derived the land surface vegetation index based on observational data from the Advanced Geostationary Radiation Imager(AGRI) onboard the FY-4B geostationary satellite. First, the AGRI reflectance of visible band and near-infrared band is corrected to the land surface reflectance by the 6S radiative transfer model. The bidirectional reflectance distribution function(BRDF) model is then used to normalize the AGRI surface reflectance at different observation angles and solar geometries, and an angle-independent reflectance is derived. The AGRI surface reflectance is further corrected to the MODIS levels according to the AGRI spectral response function(SRF). Finally, the daily AGRI data are used to synthesize the surface vegetation index. It is shown that the spatial distribution of NDVI images retrieved by single-day AGRI is consistent with that of 16-day MODIS data. At the same time, the dynamic range of the revised NDVI is closer to that of MODIS.

Innovative Analysis Ready Data(ARD)product and process requirements,software system design,algorithms and implementation at the midstream as necessary-but-notsuffcient precondition of the downstream in a new notion of Space Economy 4.0-Part 1:Problem background in Artificial General Intelligence(AGI)

Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched Analysis Ready Data(ARD)productpair and process gold standard as linchpin for success of a new notion of Space Economy 4.0.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,it is regarded as necessarybut-not-sufficient“horizontal”(enabling)precondition for:(I)Transforming existing EO big raster-based data cubes at the midstream segment,typically affected by the so-called data-rich information-poor syndrome,into a new generation of semanticsenabled EO big raster-based numerical data and vector-based categorical(symbolic,semi-symbolic or subsymbolic)information cube management systems,eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery.(II)Boosting the downstream segment in the development of an ever-increasing ensemble of“vertical”(deep and narrow,user-specific and domain-dependent)value–adding information products and services,suitable for a potentially huge worldwide market of institutional and private end-users of space technology.For the sake of readability,this paper consists of two parts.In the present Part 1,first,background notions in the remote sensing metascience domain are critically revised for harmonization across the multidisciplinary domain of cognitive science.In short,keyword“information”is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed information-as-data-interpretation.Moreover,buzzword“artificial intelligence”is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of AGI.Second,based on a betterdefined and better-understood vocabulary of multidisciplinary terms,existing EO optical sensory image-derived Level 2/ARD products and processes are investigated at the Marr five levels of understanding of an information processing system.To overcome their drawbacks,an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD product-pair and process gold standard is proposed in the subsequent Part 2.

Innovative Analysis Ready Data(ARD)product and process requirements,software system design,algorithms and implementation at the midstream as necessary-but-notsufficient precondition of the downstream in a new notion of Space Economy 4.0-Part 2:Software developments

Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this paper consists of two parts.In the previous Part 1,existing EO optical sensory imagederived Level 2/Analysis Ready Data(ARD)products and processes are critically compared,to overcome their lack of harmonization/standardization/interoperability and suitability in a new notion of Space Economy 4.0.In the present Part 2,original contributions comprise,at the Marr five levels of system understanding:(1)an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD co-product pair requirements specification.First,in the pursuit of third-level semantic/ontological interoperability,a novel ARD symbolic(categorical and semantic)co-product,known as Scene Classification Map(SCM),adopts an augmented Cloud versus Not-Cloud taxonomy,whose Not-Cloud class legend complies with the standard fully-nested Land Cover Classification System’s Dichotomous Phase taxonomy proposed by the United Nations Food and Agriculture Organization.Second,a novel ARD subsymbolic numerical co-product,specifically,a panchromatic or multispectral EO image whose dimensionless digital numbers are radiometrically calibrated into a physical unit of radiometric measure,ranging from top-of-atmosphere reflectance to surface reflectance and surface albedo values,in a five-stage radiometric correction sequence.(2)An original ARD process requirements specification.(3)An innovative ARD processing system design(architecture),where stepwise SCM generation and stepwise SCM-conditional EO optical image radiometric correction are alternated in sequence.(4)An original modular hierarchical hybrid(combined deductive and inductive)computer vision subsystem design,provided with feedback loops,where software solutions at the Marr two shallowest levels of system understanding,specifically,algorithm and implementation,are selected from the scientific literature,to benefit from their technology readiness level as proof of feasibility,required in addition to proven suitability.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,the proposed EO optical sensory image-derived semantics-enriched ARD product-pair and process reference standard is highlighted as linchpin for success of a new notion of Space Economy 4.0.