Variations In Reflectance Research Articles

Accurate estimation of camera response function for high dynamic range measurement.

A high dynamic range surface has large reflectivity variations and measuring it with a structured light technique could cause pixel saturation that will seriously degrade the measurement accuracy. Accurate identification of saturated pixels will significantly improve the measurement accuracy. This paper introduces an accurate estimation approach to the camera response function (CRF) for high dynamic range measurement and proposes a method that uses the estimated CRF to identify the saturated pixels in captured images. We perform experiments using the proposed saturation identification method and the other existing methods to compare both the saturation identification accuracy and measurement accuracy. The experiment results verify both the accuracy and suitability of the proposed method.

Suspended Palladium/Polymer Bilayer for High-Contrast and Fast Hydrogen Sensors.

Hydrogen sensing is extremely essential for hydrogen-related applications due to the explosibility of hydrogen gas (H2). Here, we first present a high-contrast and fast optical hydrogen sensor, which is a partially suspended Pd/PMMA bilayer on a PDMS substrate with a microgroove array on the surface. The suspended structure reduces constraints from the substrate on the Pd film, leading to a large wrinkling amplitude and fast response rate during hydrogenation. The PMMA film can protect the Pd film from the poisonous impurities in the air and improve the flexibility of the bilayer. When exposed to 4% H2 mixed with air, the reflectance of the sensor drops down from 43 to 4% at 600 nm wavelength, in which the corresponding reflectance contrast, defined as the ratio of the reflectances before and after exposure to hydrogen, is 10.75. Such a high reflectance variation results from the light scattering induced by the wrinkling of the suspended Pd/PMMA bilayer during hydrogenation. Meanwhile, the sensor has a fast response that the reflectance can decrease from 43 to 33% within 0.6 s. Moreover, the sensor shows good recyclability and hydrogen selectivity. These excellent performances suggest that our suspended Pd/PMMA bilayer has great potential for practical hydrogen detection.

Comparison of reflectance to solar radiation between mortars treated with TiO2 and painted mortars after three years of exposure

The incident solar radiation on the building envelope is strongly affected by the urban characteristics and building facade materials. This paper reports a study on the variation in the solar reflectance of mortar specimens with different treatments of TiO2 – powder (addition) and suspension (cover) - compared with white painted specimens and exposed in the long term. The solar reflectance of mortars was evaluated at biweekly intervals over three years to reach their degradation over time. The results obtained for the white painted specimens revealed that they practically maintained the exact value of their initial reflectance to solar radiation over three years of exposure ending with 73% of its index. In addition, the comparison between the white painted specimens and specimens with TiO2 powder addition showed a mean solar reflectance difference of 28.25%, showing that difference certainly would be noticed by the final user in terms of absorption and color change. The study also revealed that comparison between the specimens with TiO2 in powder addition and specimens with TiO2 in suspension showed a mean solar reflectance difference of 8.5% and demonstrate that result will not identify by the final user concerning the absorption and color change, and not indicate their preference since both showed the same effectiveness in mean after three years of exposure.

Detecting 2020 Coral Bleaching Event in the Northwest Hainan Island Using CoralTemp SST and Sentinel-2B MSI Imagery

In recent years, coral reef ecosystems have been affected by global climate change and human factors, resulting in frequent coral bleaching events. A severe coral bleaching event occurred in the northwest of Hainan Island, South China Sea, in 2020. In this study, we used the CoralTemp sea surface temperature (SST) and Sentinel-2B imagery to detect the coral bleaching event. From 31 May to 3 October, the average SST of the study area was 31.01 °C, which is higher than the local bleaching warning threshold value of 30.33 °C. In the difference images of 26 July and 4 September, a wide range of coral bleaching was found. According to the temporal variation in single band reflectance, the development process of bleaching is consistent with the changes in coral bleaching thermal alerts. The results show that the thermal stress level is an effective parameter for early warning of large-scale coral bleaching. High-resolution difference images can be used to detect the extent of coral bleaching. The combination of the two methods can provide better support for coral protection and research.

Analysis and evaluation of the effect of reflectance values on internal walls, internal roofs, and light shelf on optimal illumination levels in the diploma economics and business building of the vocational school UGM, Yogyakarta

The use of natural light as a source of lighting in buildings is an option in energy saving. One of the efforts that has been made is the installation of a light shelf. The light shelf installed in the UGM Vocational School Economics and Business Diploma (DEB SV) building is not fully working optimally. As many as 83% of the light shelf in lecture rooms is covered by curtains because it is considered to produce excess light (glare). This results in a greater consumption of lighting electricity. This study was conducted to analyze and evaluate the effect of the reflectance value (color) attached to the internal walls, internal roof, external light shelf, and internal light shelf on the indicator of illumination levels Useful Daylight Illuminance (UDI). Furthermore, this study aims to determine the optimum reflectance value (color) parameter. The research was conducted with a simulation method using RadianceIES in the IESVE 2021 software. The first simulation results show the value of reflectance (color) installed (base case) on the internal wall, internal roof, external light shelf, and internal light shelf in one of the lecture rooms of the DEB SV UGM building resulting in a very large value of the UDI>2000lux indicator, which is 84,9% (not according to the criteria). The results of the second simulation provide two variations of the optimum reflectance (color) parameters in the independent variable. The first variation is the internal walls, internal roof, external light shelf, and internal light shelf, each of which has a reflectance value (color) of 90,67% (beige), 100% (white), 90,67% (beige), and 100% (white). The second variation is the internal walls, internal roof, exte rnal light shelf, and internal light shelf, each of which has a reflectance value (color) of 90,67% (beige), 100% (white), 90,67% (beige), and 90,67% (beige).

Combining transfer learning and hyperspectral reflectance analysis to assess leaf nitrogen concentration across different plant species datasets

Accurate estimation of leaf nitrogen concentration (LNC) is critical to characterize ecosystem and plant physiological processes for example in carbon fixation. Remote sensing can capture LNC, while interrelated traits and spectral diversity across plant species prevent development of transferable LNC assessment models based on leaf reflectance. Here, we developed a new transfer learning method by coupling transfer component analysis with the support vector regression, namely TCA-SVR, to transfer LNC assessment models across different plant species. We benchmarked the performance of TCA-SVR against a well-established partial least squares regression (PLSR) model with five remote sensing datasets on 60 plant species measured from three spectroradiometers with varied spectral resolutions and illumination and viewing angles. The result showed that leaf reflectance presented the high spectral diversity in different spectral regions, plant species, and growth stages. The combination of visible (VIS), near infrared (NIR), and shortwave infrared (SWIR) reflectance (e.g. 550–2300 nm) achieved the optimal LNC assessment across all datasets. Results on the testing datasets showed that the transferability of the PLSR models highly depended on the LNC distribution and spectral features, which were associated with the differences in plant species, spectral measurements, and growth conditions between datasets. These differences led to the large variations in LNC and leaf reflectance, which thus produced the overestimations and underestimations of LNC. Compared to the PLSR model, TCA-SVR greatly improved the transferability of the LNC assessment model by reducing the average root mean square error by 36.76%. Further, the implementation of modeling updating can help TCA-SVR learn the features related to the difference in plant species and LNC ranges by transferring samples from the target dataset to the source dataset. Our model updating approach improved the performance of TCA-SVR and only needed 5% of the off-site samples to supplement the source dataset to achieve an effective assessment of LNC. Refining the proposed method with new remote sensing datasets will aid rapid monitoring of plant nitrogen status and may improve carbon‑nitrogen interactions in existing ecosystem models.

Thermal Maturity of the Grajcarek Unit (Pieniny Klippen Belt): Insights for the Burial History of a Major Tectonic Boundary of the Western Carpathians

The Grajcarek Unit of the Pieniny Klippen Belt (PKB), at the boundary between the Central (Inner) and Outer Carpathians, resulted from the convergence of the ALCAPA (the Alps–Carpathians–Pannonia) block and European plate. The strongly deformed slices of the Grajcarek Unit consist of Jurassic–Cretaceous sedimentary rocks associated with Late Cretaceous–Middle Palaeocene synorogenic wild-flysch, and sedimentary breccias with olistoliths. Maximum burial temperatures and burial depths were estimated based on vitrinite reflectance data. The vitrinite reflectance values were wide scattered through the Grajcarek sedimentary succession, especially in the flysch formations. This is attributed mainly to the depositional effects that affected the vitrinite evolution. The determined maximum burial temperatures were interpreted due to the regional compression controlled by tectonic burial coeval with thrusting and strike-slip faulting. The regional vitrinite reflectance variations might estimate cumulative displacement around the NNW–SSE and oriented the strike-slip Dunajec fault, which is a continuation of the deep fracture Kraków–Myszków fault zone.

Development of a high frequency ultrasonic setup for measuring the parameters of thin films

In this report a novel method for measuring the elastic properties of thin 10 nm films is described. The method is based on the use of a nanosecond laser for generation acoustic waves in solids. Absorption of the incident laser pulse energy and the associated temperature gradients induces a rapidly changing strain field. This strain field, in turn, radiates energy as elastic (ultrasonic) waves. At low pulse power, this is an entirely thermo elastic process resulting in no damage to the sample. The acoustic echo arriving at the probed surface causes both the displacement of the surface (a few nanometres) and the strain in the subsurface material, which might be detected through the variation of the optical reflectivity of the material, i.e. through the acousto-optic effect.

Enhanced Refractive Index Sensitivity through Combining a Sol-Gel Adsorbate with a TiO2 Nanoimprinted Metasurface for Gas Sensing.

We combine a gas-adsorbent microporous hybrid silica layer and a dense TiO2 Mie resonator array (metasurface), both obtained by sol-gel deposition and nanoimprint lithography, to form nanocomposite systems with high sensitivity for refractive index (RI) variations induced by gas adsorption. Using optical transduction based on direct specular reflection, we show spectral shifts of 4470 nm/RIU corresponding to 0.2 nm/ppm gas (air concentration) and reflection intensity changes of R* = 17 (R/RIU) and 0.55 × 10-3 R/ppm (air concentration). The metasurface is composed of hexagonally arranged TiO2 nanopillar arrays, whereas the surrounding sensitive material is a class II microporous hybrid silica, containing methyl and phenyl covalently bonded organic functions. This hybrid layer shows efficient adsorption capability of volatile organic molecules such as isopropanol, which is used to induce slight variations of RI around the TiO2 antennas. Specular reflectance variations at 45° incidence and refractive index measurements are performed using a spectroscopic ellipsometer. The presence of the titania metasurface enhances the signal by almost an order of magnitude with respect to the 2D counterpart (simulated as an effective medium approximation) and is attributed to the antenna effect, enhancing the interaction of the confined electromagnetic wave with the sensitive microporous medium. This sol-gel nanocomposite system presents many advantages such as high throughput and low-cost elaboration of elements and a high chemical, mechanical, and thermal resistance, ensuring high stability as a potential gas-sensitive nanocomposite layer for long periods. This work is a case study of improving the sensitivity of sol-gel gas-sensitive materials in optical transduction, which will be exploited in further works to develop artificial noses.

A Method to Estimate Surface Soil Moisture and Map the Irrigated Cropland Area Using Sentinel-1 and Sentinel-2 Data

Considering variations in surface soil moisture (SSM) is essential in improving crop yield and irrigation scheduling. Today, most remotely sensed soil moisture products have difficulties in resolving irrigation signals at the plot scale. This study aims to use Sentinel-1 radar backscatter and Sentinel-2 multispectral imagery to estimate SSM at high spatial (10 m) and temporal resolution (at least 5 days) over an agricultural domain. Three supervised machine learning algorithms, multilayer perceptron (MLP), a convolutional neural network (CNN), and linear regression models, were trained to estimate changes in SSM based on the variation in surface reflectance and backscatter over five different crops. Results showed that CNN is the best algorithm as it understands spatial relations and better represents two-dimensional images. Estimated values for SSM were in agreement with in-situ measurements regardless of the crop type, with RMSE=0.0292 (cm3/cm3) and R2=0.92 for the Sentinel-2 derived SSM and RMSE=0.0317 (cm3/cm3) and R2=0.84 for the Sentinel-1 soil moisture data. Moreover, a time series of estimated SSM based on Sentinel-1 (SSM-S1), Sentinel-2 (SSM-S2), and SSM derived from SMAP-Sentinel1 was compared. The developed SSM data showed a significantly higher mean SSM state over irrigated agriculture relative to the rainfed cropland area during the irrigation season. The multiple comparisons (fisher LSD) were tested and found that these two groups are different (pvalue=0.035 in 95% confidence interval). Therefore, by employing the maximum likelihood classification on the SSM data, we managed to map the irrigated agriculture. The overall accuracy of this unsupervised classification is 77%, with a kappa coefficient of 65%.

An Angular Displacement Sensor-Based Active Feedback Open Complementary Split-Ring Resonator

This letter presents an active feedback microwave sensor with a wide dynamic range and high sensitivity for detecting angular displacement. The sensor comprises two types of movable ring resonators (the rotor), split-ring resonator (SRR) and complement SRR (CSRR), and a modified convex-shaped open complementary split-ring resonator (the stator). The stator is designed with an active circuitry to enhance the quality factor over 4.7 K, and the feedback loop surrounds the sensing zone to enhance the mutual coupling for tracking a finite rotation of rotors in a wide dynamic range. The stator uses the separation between two reflection coefficients or the decibel magnitude variation at a fixed frequency, which is generated from its resonance frequency shift and whose values vary as a function of the rotation angle to be measured. After rotor loading, the average decibel sensitivity in terms of variation in reflection was calculated as 0.32 and 0.13 dB/degree for the SRR and CSRR, respectively, within a dynamic range of 0°–90°.

Novel monkey-wrench-shaped microstrip patch sensor for food evaluation and analysis.

Microwave sensor technology is considered to be a non-destructive and hygienic means for food evaluation and analysis. The rapid progress in microwave sensor technologies motivated us to present a novel monkey-wrench-shaped microstrip patch sensor for evaluating food quality. The proposed antenna is considered as a liquid sensor to detect adulteration in liquids by examining the relationship between concentration, shift in resonant frequency, and variation in reflection coefficient. The sensor has a compact size of 17 × 14 mm2 imprinted on an FR4 substrate of thickness 1.57 mm. This microwave system is proposed for monitoring overall milk quality using a microstrip sensor and has considerably good numerical sensitivity and accuracy (13.11% and 88.5% respectively), which makes the system attractive for detecting adulteration. Further, the Q-factor for the proposed sensor is 209 and has a standard deviation less than the difference between non-adulterated and adulterated values, giving resolution high enough to distinguish adulteration with an acceptable statistical accuracy. In this study, different milk categories (buffalo, goat, and cow milk) are considered as liquid samples to detect adulteration by demonstrating the variation in reflection coefficient due to change in dielectric properties for the following different cases: (i) adulteration of milk with water; (ii) adulteration of milk with synthetic milk powder; (iii) adulteration of milk with caustic soda; and (iv) adulteration of milk with vegetable oil. The referred variation in reflection coefficient and resonant frequency is due to a change in the dielectric properties of a liquid when a varying concentration of an adulterant/solute is added to the liquid sample. The simulation and measured results show good agreement that validates the proposed sensor for food adulteration detection with high sensitivity. In terms of performance, the proposed sensor shows accuracy with high spatial resolution and reduced penetration depth to detect the adulteration in various milk samples (i.e. buffalo, goat, and cow milk). © 2021 Society of Chemical Industry.

Mapping Nighttime and All-Day Radiative Cooling Potential in Europe and the Influence of Solar Reflectivity

Radiative cooling is a natural process to cool down surfaces through the rejection of thermal radiation using the outer space as a cold sink, taking advantage of the transparency of the atmospheric windows (8–14 μm), which partially matches the infrared radiation band. With the development of new materials that have a high reflectivity of solar radiation, daytime radiative cooling can be achieved. This phenomenon depends on the optical properties of the surface and the local weather conditions. In this research, climatological data from 1791 weather stations were used to present detailed nighttime and all-day radiative cooling maps for the potential implementation of radiative cooling-based technologies. The paper offers a parametric study of the variation of the potential as a result of decreasing the solar reflectivity. The results show that southern Europe is the region with the highest potential while northern Europe holds more hours of available radiative cooling. After varying the solar reflectivity from 1 to 0.5 the average power reduces from 60.18 to 45.32 W/m2, and energy from 527.10 to 264.87 kWh/m2·year. For solar reflectivity lower than 0.5, all-day radiative coolers behave as nighttime radiative coolers, but power and energy values improve significantly for high values of solar reflectivity. Small variations of solar reflectivity have greater impacts on the potential at higher reflectivity values than at lower ones.

Numerical Study on Surface Roughness Measurement Based on Nonlinear Ultrasonics in Through-Transmission and Pulse-Echo Modes.

Ultrasonic is one of the well-known methods for surface roughness measurement, but small roughness will only lead to a subtle variation of transmission or reflection. To explore sensitive techniques for surfaces with small roughness, nonlinear ultrasonic measurement in through-transmission and pulse-echo modes was proposed and studied based on an effective unit-cell finite element (FE) model. Higher harmonic generation in solids was realized by applying the Murnaghan hyperelastic material model. This FE model was verified by comparing the absolute value of the nonlinearity parameter with the analytical solution. Then, random surfaces with different roughness values ranging from 0 μm to 200 μm were repeatedly generated and studied in the two modes. The through-transmission mode is very suitable to measure the surfaces with roughness as small as 3% of the wavelength. The pulse-echo mode is sensitive and effective to measure the surface roughness ranging from 0.78% to 5.47% of the wavelength. This study offers a potential nondestructive testing and monitoring method for the interfaces or inner surfaces of the in-service structures.

Morlet Wavelet Filtering and Phase Analysis to Reduce the Limit of Detection for Thin Film Optical Biosensors

The ultimate detection limit of optical biosensors is often limited by various noise sources, including those introduced by the optical measurement setup. While sophisticated modifications to instrumentation may reduce noise, a simpler approach that can benefit all sensor platforms is the application of signal processing to minimize the deleterious effects of noise. In this work, we show that applying complex Morlet wavelet convolution to Fabry-Pérot interference fringes characteristic of thin film reflectometric biosensors effectively filters out white noise and low-frequency reflectance variations. Subsequent calculation of the average difference in extracted phase between the filtered analyte and reference signals enables a significant reduction in the limit of detection (LOD). This method is applied on experimental data sets of thin film porous silicon sensors (PSi) in buffered solution and complex media obtained from two different laboratories. The demonstrated improvement in the LOD achieved using wavelet convolution and average phase difference paves the way for PSi optical biosensors to operate with clinically relevant detection limits for medical diagnostics, environmental monitoring, and food safety.

Tunable graphene-based metasurface for an ultra-low sidelobe terahertz phased array antenna.

In this paper, we propose an all-solid-state, electrically tunable, and reflective graphene metasurface array that can generate a specific phase or continuous scanning between 0° and 352.5° in the terahertz band. By optimizing the structural parameters of the metasurface, the average reflectivity can reach 68.3%, and the maximum reflectivity variation range is only 30%. We also simulate the results that an electrically tunable terahertz phased array can be achieved by adjusting the Fermi levels of a monolayer graphene resonator. The maximum deflection of the reflected beam is 46.05°, and the resolution can be improved to 1.10°. It should be noted that the sidelobe energy only accounts for 1.06% of the main lobe energy, due to the slight change in reflectivity with the phase gradient.

Uncertainties in measurements of leaf optical properties are small compared to the biological variation within and between individuals of European beech

The measurement of leaf optical properties (LOP) using reflectance and scattering properties of light allows a continuous, time-resolved, and rapid characterization of many species traits including water status, chemical composition, and leaf structure. Variation in trait values expressed by individuals result from a combination of biological and environmental variations. Such species trait variations are increasingly recognized as drivers and responses of biodiversity and ecosystem properties. However, little has been done to comprehensively characterize or monitor such variation using leaf reflectance, where emphasis is more often on species average values. Furthermore, although a variety of platforms and protocols exist for the estimation of leaf reflectance, there is neither a standard method, nor a best practise of treating measurement uncertainty which has yet been collectively adopted. In this study, we investigate what level of uncertainty can be accepted when measuring leaf reflectance while ensuring the detection of species trait variation at several levels: within individuals, over time, between individuals, and between populations. As a study species, we use an economically and ecologically important dominant European tree species, namely Fagus sylvatica. We first use fabrics as standard material to quantify measurement uncertainties associated with leaf clip (0.0001 to 0.4 reflectance units) and integrating sphere measurements (0.0001 to 0.01 reflectance units) via error propagation. We then quantify spectrally resolved variation in reflectance from F. sylvatica leaves. We show that the measurement uncertainty associated with leaf reflectance, estimated using a field spectroradiometer with attached leaf clip, represents on average a small portion of the spectral variation within a single individual sampled over one growing season (2.7 ± 1.7%), or between individuals sampled over one week (1.5 ± 1.3% or 3.4 ± 1.7%, respectively) in a set of monitored F. sylvatica trees located in Swiss and French forests. In all forests, the spectral variation between individuals exceeded the spectral variation of a single individual at the time of the measurement. However, measurements of variation within individuals at different canopy positions over time indicate that sampling design (e.g., standardized sampling, and sample size) strongly impacts our ability to measure between-individual variation. We suggest best practice approaches toward a standardized protocol to allow for rigorous quantification of species trait variation using leaf reflectance.

Cone photoreceptor reflectance variation in the northern tree shrew and thirteen-lined ground squirrel.

In vivo images of human cone photoreceptors have been shown to vary in their reflectance both spatially and temporally. While it is generally accepted that the unique anatomy and physiology of the photoreceptors themselves drives this behavior, the exact mechanisms have not been fully elucidated as most studies on these phenomena have been limited to the human retina. Unlike humans, animal models offer the ability to experimentally manipulate the retina and perform direct in vivo and ex vivo comparisons. The thirteen-lined ground squirrel and northern tree shrew are two emerging animal models being used in vision research. Both models feature cone-dominant retinas, overcoming a key limitation of traditional rodent models. Additionally, each possesses unique but well-documented anatomical differences in cone structure compared to human cones, which can be leveraged to further constrain theoretical models of light propagation within photoreceptors. Here we sought to characterize the spatial and temporal reflectance behavior of cones in these species. Adaptive optics scanning light ophthalmoscopy (AOSLO) was used to non-invasively image the photoreceptors of both species at 5 to 10 min intervals over the span of 18 to 25 min. The reflectance of individual cone photoreceptors was measured over time, and images at individual time points were used to assess the variability of cone reflectance across the cone mosaic. Variability in spatial and temporal photoreceptor reflectance was observed in both species, with similar behavior to that seen in human AOSLO images. Despite the unique cone structure in these animals, these data suggest a common origin of photoreceptor reflectance behavior across species. Such data may help constrain models of the cellular origins of photoreceptor reflectance signals. These animal models provide an experimental platform to further explore the morphological origins of light capture and propagation.

Optical, morphological, physical and crystalline properties of type structures CexAl2-xO3 (x = 0; 0.25; 0.50; 0.75 and 1) obtained by microwave assisted combustion

Cerium aluminate is a perovskite type that presents AmBnO3 that has interesting physical, morphological properties and crystalline structures; however it has not been deeply studied when synthesized by microwave-assisted self-combustion specifically. Thus, the objective of this work was to synthesize CeAlO3 by microwave-assisted combustion method in an one-step using only one fuel (urea, 250% excess). Formulations were identified by CexAl2-xO3 (x = 0, 0.25, 0.50, 0.75 and 1; in mol), an α-Al2O3–standard was used how reference. X-ray diffraction (XRD), scanning electron microscopy (SEM-EDS and SEM-FEG), specific gravity, absorption spectroscopy in the ultraviolet and visible region (diffuse reflection), Fourier transform infrared spectroscopy (FTIR) and Raman were the techniques used in the characterizations. The results show that CeAlO3 was formed in the synthesis, as well as CeAl11O18 and CeO2 phase. In the diffuse reflection of light, the beginning of the increase in reflectivity occurs at wavelengths close to 380 nm and band-gap between 3.36 to 3.47 eV; the presence of microstructural and macrostructural defects impacted on the variation of reflectivity in the UV–visible region and on the variation of densities (5.06–5.96 g.cm−³); heterogeneous morphologies expressed by diversified surfaces, particulates tending to equiaxial symmetry and perforation signals, in addition to prismatic crystals growing parallel to the surface. The FTIR confirms the formations of α-Al2O3 and Raman confirms the presence of residual carbon. These results are relevant, since the work produced perovskites with stable structures in a single step, optimizing the manufacturing process of these materials with the elimination of calcination after synthesis.

Reflection and transmission of three-dimensional plane wave between distinct fiber-reinforced medium under initial stress

The present concept is related to reflection and refraction phenomena of a three-dimensional plane quasi-P wave incident at the interface between distinct fiber-reinforced medium under the influence of initial stress. The expressions of all the phase velocities of reflected and transmitted quasi-P (qP), and quasi shear waves (qS1 and qS2) are derived analytically. The amplitude ratios of reflected and transmitted quasi waves are also obtained in compact form. The expressions are computed numerically to show the effect of initial stress and the reinforcement parameter on the reflection and refraction coefficients. Also, the variations of reflection and transmission coefficients and the energy coefficients with the incidence angle have been shown by plotting two-dimensional graphs.