Search Results (23)

Accurate solar background noise modeling in island-reef LiDAR surveys is hindered by anisotropic coastal reflectivity and dynamic light paths, which isotropic models fail to address. We propose BNR-B, a bidirectional reflectance distribution function (BRDF)-based noise model that integrates solar-receiver geometry with micro-facet scattering dynamics. Validated via single-photon LiDAR field tests on diverse coastal terrains at Jiajing Island, China, BNR-B reveals the following: (1) Solar zenith/azimuth angles non-uniformly modulate noise fields—higher solar zenith angles reduce noise intensity and homogenize spatial distribution; (2) surface reflectivity linearly correlates with noise rate (R² > 0.99), while roughness governs scattering directionality through micro-facet redistribution. BNR-B achieves 28.6% higher noise calculation accuracy than Lambertian models, with a relative phase error < 2% against empirical data. As the first BRDF-derived solar noise correction framework for coastal LiDAR, it addresses critical limitations of isotropic assumptions by resolving directional noise modulation. The model’s adaptability to marine–terrestrial interfaces enhances precision in coastal monitoring and submarine mapping, offering transformative potential for geospatial applications requiring photon-counting LiDAR in complex environments. Key innovations include dynamic coupling of geometric optics and surface scattering physics, enabling robust spatiotemporal noise quantification, critical for high-resolution terrain reconstruction. Full article

This study analyzes the impact of powder-blasted surface modification on the performance of non-imaging solar concentrators and evaluates a ray-tracing simulation approach to virtual solar power measurements. Powder blasting was applied to poly(methyl methacrylate) (PMMA) sheets to create a rough, Lambertian-like scattering surface, enhancing light trapping and total internal reflection. The effects of this modification were systematically assessed using optical transmission spectroscopy, angular scattering measurements, and solar cell efficiency characterization under standard AM1.5 illumination. The results show that surface roughening significantly improves light redirection toward the concentrator’s edge, enhancing solar cell performance. OptisWorks ray-tracing simulations were employed to model the concentrator’s optical behavior, demonstrating strong agreement (within 5–10% deviation) with experimental data. These findings confirm that surface modification is crucial in optimizing concentrator efficiency and establishing ray tracing as a reliable tool for virtual performance evaluation in photovoltaic applications. Full article

The proliferation of AI-generated content (AIGC) has empowered non-experts to create highly realistic Deepfake images and videos using user-friendly software, posing significant challenges to the legal system, particularly in criminal investigations, court proceedings, and accident analyses. The absence of reliable Deepfake verification methods threatens the integrity of legal processes. In response, researchers have explored deep forgery detection, proposing various forensic techniques. However, the swift evolution of deep forgery creation and the limited generalizability of current detection methods impede practical application. We introduce a new deep forgery detection method that utilizes image decomposition and lighting inconsistency. By exploiting inherent discrepancies in imaging environments between genuine and fabricated images, this method extracts robust lighting cues and mitigates disturbances from environmental factors, revealing deeper-level alterations. A crucial element is the lighting information feature extractor, designed according to color constancy principles, to identify inconsistencies in lighting conditions. To address lighting variations, we employ a face material feature extractor using Pattern of Local Gravitational Force (PLGF), which selectively processes image patterns with defined convolutional masks to isolate and focus on reflectance coefficients, rich in textural details essential for forgery detection. Utilizing the Lambertian lighting model, we generate lighting direction vectors across frames to provide temporal context for detection. This framework processes RGB images, face reflectance maps, lighting features, and lighting direction vectors as multi-channel inputs, applying a cross-attention mechanism at the feature level to enhance detection accuracy and adaptability. Experimental results show that our proposed method performs exceptionally well and is widely applicable across multiple datasets, underscoring its importance in advancing deep forgery detection. Full article

Due to the presence of regions with weak textures or non-Lambertian surfaces, feature matching in learning-based Multi-View Stereo (MVS) algorithms often leads to incorrect matches, resulting in the construction of the flawed cost volume and incomplete scene reconstruction. In response to this limitation, this paper introduces the MVS network based on attention mechanism and neural volume rendering. Firstly, we employ a multi-scale feature extraction module based on dilated convolution and attention mechanism. This module enables the network to accurately model inter-pixel dependencies, focusing on crucial information for robust feature matching. Secondly, to mitigate the impact of the flawed cost volume, we establish a neural volume rendering network based on multi-view semantic features and neural encoding volume. By introducing the rendering reference view loss, we infer 3D geometric scenes, enabling the network to learn scene geometry information beyond the cost volume representation. Additionally, we apply the depth consistency loss to maintain geometric consistency across networks. The experimental results indicate that on the DTU dataset, compared to the CasMVSNet method, the completeness of reconstructions improved by 23.1%, and the Overall increased by 7.3%. On the intermediate subset of the Tanks and Temples dataset, the average F-score for reconstructions is 58.00, which outperforms other networks, demonstrating superior reconstruction performance and strong generalization capability. Full article

The standard photometric stereo model makes several assumptions that are rarely verified in experimental datasets. In particular, the observed object should behave as a Lambertian reflector, and the light sources should be positioned at an infinite distance from it, along a known direction. Even when Lambert’s law is approximately fulfilled, an accurate assessment of the relative position between the light source and the target is often unavailable in real situations. The Hayakawa procedure is a computational method for estimating such information directly from data images. It occasionally breaks down when some of the available images excessively deviate from ideality. This is generally due to observing a non-Lambertian surface, or illuminating it from a close distance, or both. Indeed, in narrow shooting scenarios, typical, e.g., of archaeological excavation sites, it is impossible to position a flashlight at a sufficient distance from the observed surface. It is then necessary to understand if a given dataset is reliable and which images should be selected to better reconstruct the target. In this paper, we propose some algorithms to perform this task and explore their effectiveness. Full article

Converting the actual scenes into three-dimensional models has inevitably become one of the fundamental requirements in autonomous driving. At present, the main obstacle to large-scale deployment is the high-cost lidar for environment sensing. Monocular depth estimation aims to predict the scene depth and construct a 3D map via merely a monocular camera. In this paper, we add geometric consistency constraints to address the non-Lambertian surface problems in depth estimation. We also utilize the imaging principles and conversion rules to produce a 3D scene model from multiple images. We built a prototype and conduct extensive experiments in a corridor and an underground parking structure, and the results show the effectiveness for indoor location-based services. Full article

Six-dimensional pose estimation for non-Lambertian objects, such as metal parts, is essential in intelligent manufacturing. Current methods pay much less attention to the influence of the surface reflection problem in 6D pose estimation. In this paper, we propose a cross-attention-based reflection-aware 6D pose estimation network (CAR6D) for solving the surface reflection problem in 6D pose estimation. We use a pseudo-Siamese network structure to extract features from both an RGB image and a 3D model. The cross-attention layers are designed as a bi-directional filter for each of the inputs (the RGB image and 3D model) to focus on calculating the correspondences of the objects. The network is trained to segment the reflection area from the object area. Training images with ground-truth labels of the reflection area are generated with a physical-based rendering method. The experimental results on a 6D dataset of metal parts demonstrate the superiority of CAR6D in comparison with other state-of-the-art models. Full article

Polarimetric synthetic aperture radar (PolSAR) data provide an alternative way for topography retrieval, especially when limited PolSAR data are available. This article proposes a novel topography retrieval algorithm based on the Lambertian backscatter model that further improves the vertical precision of digital elevation model (DEM) generation and requires only one flight. The key idea of the proposed algorithm is to avoid data fluctuations caused by the ratio of the azimuth slope angle to the polarimetric orientation angle (POA). The previous research has confirmed the feasibility of generating a DEM based on single-pass PolSAR data, but its effect on the quality of reference DEM has not been well-explained. To analyze this effect, a large number of experiments on DEM with different resolutions are conducted. In addition, an in-depth analysis of non-linear and terrain-dependent errors is performed. The L-band PolSAR data of NASA/JPL TOPSAR and ALOS-2 PALSAR-2 and interferometric SAR (InSAR) DEM data are used to verify the proposed algorithm. The experimental results show that PolSAR data can be used as an additional reliable information source for DEM fusion under certain conditions to improve the quality of public DEM. Full article

The Bidirectional Reflectance Distribution Function (BRDF) is usually used to describe the reflectance anisotropy of a non-Lambertian surface and estimate surface parameters. Among the BRDF models, the kernel-driven models have been extensively used due to their simple form and powerful fitting ability, and their reliability has been validated in some studies. However, existing validation efforts used in situ measurements or limited satellite data, which may be subject to inadequate observational conditions or quality uncertainties. A recently released high-quality BRDF database from Polarization and Directionality of the Earth’s Reflectances (POLDER) provides an opportunity to revisit the performance of the kernel-driven models. Therefore, in order to evaluate the fitting ability of the kernel-driven models under different observational conditions and explore their application direction in the future, we use the filtered high-quality BRDF database to evaluate the fitting ability of the kernel-driven model represented by the RossThick-LiSparseR (RTLSR) kernels in this paper. The results show that the RTLSR model performs well, which shows small fitting residuals under most observational conditions. However, the applicability of the RTLSR model performed differently across land cover types; the RTLSR model exhibited larger fitting residuals, especially over non-vegetated surfaces. Under different sun-sensor geometries, the fitting residuals show a strong positive correlation with the Solar Zenith Angle. The above two factors cause the RTLSR model to exhibit a poorer fitting ability at high latitudes. As an exploration, we designed a model combination strategy that combines the advantages of different models and achieved a better performance at high latitudes. We believe that this study provides a better understanding of the RTLSR model. Full article

This paper presents a photometric stereo (PS) method based on the dichromatic reflectance model (DRM) using colour images. The proposed method estimates surface orientations for surfaces with non-Lambertian reflectance using diffuse-specular separation and contains two steps. The first step, referred to as diffuse-specular separation, initialises surface orientations in a specular invariant colour subspace and further separates the diffuse and specular components in the RGB space. In the second step, the surface orientations are refined by first initialising specular parameters via solving a log-linear regression problem owing to the separation and then fitting the DRM using Levenburg-Marquardt algorithm. Since reliable information from diffuse reflection free from specularities is adopted in the initialisations, the proposed method is robust and feasible with less observations. At pixels where dense non-Lambertian reflectances appear, signals from specularities are exploited to refine the surface orientations and the additionally acquired specular parameters are potentially valuable for more applications, such as digital relighting. The effectiveness of the newly proposed surface normal refinement step was evaluated and the accuracy in estimating surface orientations was enhanced around $30\%$ on average by including this step. The proposed method was also proven effective in an experiment using synthetic input images comprised of twenty-four different reflectances of dielectric materals. A comparison with nine other PS methods on five representative datasets further prove the validity of the proposed method. Full article

Shape-from-Shading represents the problem of computing the three-dimensional shape of a surface given a single gray-value image of it as input. In a recent paper, we showed that the introduction of an attenuation factor in the brightness equations related to various perspective Shape-from-Shading models allows us to ensure the well-posedness of the corresponding differential problems. Here, we propose a unified convergence result of a numerical scheme for several non-Lambertian reflectance models. This result is interesting since it can be easily extended to other non-Lambertian models in a unified and, therefore, powerful framework. Full article

The study focused on increasing the efficiency of germicidal UV radiation by using highly diffuse reflective materials such as PTFE in irradiated cavities of UV air purifiers. In a conventional cylindrically symmetric cavity with a linear amalgam mercury lamp as UV-radiation source on the axis UV-radiation, flux directed from the lamp to the walls dropped from the axis to the periphery. To increase the UV irradiation, the walls are often made mirror-reflective, but the radiation flux distribution remained radially symmetric with a maximum on the source emitting surface in this case as well. When most of the emitted light is returned to the source after one reflection, the conditions of its operation are disturbed. If the walls are made of highly diffuse reflective materials, the radiation flux density inside the cavity increases on average, and its distribution becomes uniform and highly symmetric. Thus, the effect of amplification of the radiation flux due to the highly diffuse reflectivity of the walls increases with radius and reaches a maximum at the wall. Experiments were performed to demonstrate increasing amplification of germicidal UV radiation flux with a diffuse reflection coefficient in cylindrical cavities with walls of PTFE and ePTFE. The irradiation of the cavity wall was observed to increase up to 20 times at the resonant mercury line of 253.7 nm and up to 40 times at some non-resonant lines of the visible range due to highly diffuse reflectivity of the cavity walls. The flux amplification effect was limited by the diffuse reflectivity value of the walls and absorption coefficient of the radiation emitting surface. A formula for calculating the radiation flux amplification factor in a diffusely reflecting cylindrically symmetric cavity was derived for the case of Lambertian source and reflector, including wall reflectivity and source surface absorption coefficients. The effects of heating and cooling of the mercury lamp amalgam directly affected the amplification, and symmetrization of germicidal irradiation was observed and is discussed in the paper. Numerical calculations were performed by the ray tracing method. The calculated model was verified by comparing the numerical results with those of both the approximate theoretical consideration and experiments. The promising use of diffusely reflecting cylindrical cavities for UV air purifiers is discussed. Designs of air inlet and outlet ports that allow effective locking of germicidal radiation inside the UV air purifiers were considered. The results of this work may be of interest for further developments in the UV disinfection technique. Full article

Under 5G envision, for pushing visible light communication (VLC) channel model evolution to various non-Lambertian beams, this paper introduces the typical commercial non-Lambertian beams, such as Luxeon rebel and side emitter, into the conventional analytical VLC channel model. The numerical results illustrate that the non-Lambertian beams can significantly affect the VLC channel frequency response characteristics. Compared with the traditional Lambertian beam, Side Emitter optical beam could naturally bring up to about 56.8% VLC multi input multi output channel capacity deviation, which objectively opens a new discussion dimension for enhancing VLC transmission performance. Full article

This study focuses on the recovery of information from shadowed pixels in RGB or multispectral imagery sensed from unmanned aerial vehicles (UAVs). The proposed technique is based on the concept that a property characterizing a given surface is its spectral reflectance, i.e., the ratio between the flux reflected by the surface and the radiant flux received by the surface, and this ratio is usually similar under direct-plus-diffuse irradiance and under diffuse irradiance when a Lambertian behavior can be assumed. Scene-dependent elements, such as trees, shrubs, man-made constructions, or terrain relief, can block part of the direct irradiance (usually sunbeams), in which part of the surface only receives diffuse irradiance. As a consequence, shadowed surfaces comprising pixels of the image created by the UAV remote sensor appear. Regardless of whether the imagery is analyzed by means of photointerpretation or digital classification methods, when the objective is to create land cover maps, it is hard to treat these areas in a coherent way in terms of the areas receiving direct and diffuse irradiance. The hypothesis of the present work is that the relationship between irradiance conditions in shadowed areas and non-shadowed areas can be determined by following classical empirical line techniques for fulfilling the objective of a coherent treatment in both kinds of areas. The novelty of the presented method relies on the simultaneous recovery of information in non-shadowed and shadowed areas by the in situ spectral reflectance measurements of characterized Lambertian targets followed by smoothing of the penumbra area. Once in the lab, firstly, we accurately detected the shadowed pixels by combining two well-known techniques for the detection of the shadowed areas: (1) using a physical approach based on the sun’s position and the digital surface model of the area covered by the imagery; and (2) the image-based approach using the histogram properties of the intensity image. In this paper, we present the benefits of the combined usage of both techniques. Secondly, we applied a fit between non-shadowed and shadowed areas by using a twin set of spectrally characterized target sets. One set was placed under direct and diffuse irradiance (non-shadowed targets), whereas the second set (with the same spectral characteristics) was placed under diffuse irradiance (shadowed targets). Assuming that the reflectance of the homologous targets of each set was the same, we approximated the diffuse incoming irradiance through an empirical line correction. The model was applied to all detected shadowed areas in the whole scene. Finally, a smoothing filter was applied to the penumbra transitions. The presented empirical method allowed the operational and coherent recovery of information from shadowed areas, which is very common in high-resolution UAV imagery. Full article

The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects. Full article