BTF Modelling Using BRDF Texels

A rough texture modelling involves a huge image data-set - the bidirectional texture function (BTF). This 6-dimensional function depends on planar texture coordinates as well as on view and illumination angles. We propose a new non-linear reflectance model, based on a Lafortune reflectance model improvement, which restores all BTF database images independently for each view position and herewith significantly reduces stored BTF data size. The extension consists in introducing several spectral parameters for each BTF image which are linearly estimated in the second estimation step according to the original data. The model parameters are computed for every surface reflectance field contained in the original BFT data. This technique allows BTF data compression by the ratio 1:15 while the synthesised images are almost indiscernible from the originals. The method is universal, and easily implementable in a graphical hardware for the purpose of real-time BTF rendering.

In this work, we investigate the visual appearance of real-world surfaces and the dependence of appearance on the geometry of imaging conditions. We discuss a new texture representation called the BTF (bidirectional texture function) which captures the variation in texture with illumination and viewing direction. We present a BTF database with image textures from over 60 different samples, each observed with over 200 different combinations of viewing and illumination directions. We describe the methods involved in collecting the database as well as the importqance and uniqueness of this database for computer graphics. A related quantity to the BTF is the familiar BRDF (bidirectional reflectance distribution function). The measurement methods involved in the BTF database are conducive to simultaneous measurement of the BRDF. Accordingly, we also present a BRDF database with reflectance measurements for over 60 different samples, each observed with over 200 different combinations of viewing and illumination directions. Both of these unique databases are publicly available and have important implications for computer graphics.

We propose an efficient method for editing bidirectional texture functions (BTFs) based on edit propagation scheme. In our approach, users specify sparse edits on a certain slice of BTF. An edit propagation scheme is then applied to propagate edits to the whole BTF data. The consistency of the BTF data is maintained by propagating similar edits to points with similar underlying geometry/reflectance. For this purpose, we propose to use view independent features including normals and reflectance features reconstructed from each view to guide the propagation process. We also propose an adaptive sampling scheme for speeding up the propagation process. Since our method needn't any accurate geometry and reflectance information, it allows users to edit complex BTFs with interactive feedback.

Bidirectional Texture Functions (BTFs) provide a realistic depiction of the appearance of many real-world materials as they contain the spatially varying light scattering behavior of the material surface. Since editing of existing BTF data is still in its early stages, materials have to be measured from real-world samples. In contrast to the related Spatially Varying BRDFs (SVBRDFs), the reflectance information encoded in a BTF also includes non-local scattering effects and therefore does not obey energy conservation or reciprocity. While this higher degree of freedom also contributes to an increased realism, it inadvertently calls for an extensive measurement of reflectance samples, as many regularization approaches from BRDF measurement do not apply. In this paper, we present an automated, parallelized, robust, fast and transportable setup for the acquisition of BTFs from flat samples as well as 3D objects using camera and light arrays: the DOME II. In contrast to previous camera array approaches, the present setup, which is comprised of high-quality industry grade components, overcomes several issues regarding stability, reliability and precision. It achieves a well balanced state-of-the-art acquisition performance in terms of speed and quality at reasonable costs.

We present a system for decorating arbitrary surfaces with bidirectional texture functions (BTF). Our system generates BTFs in two steps. First, we automatically synthesize a BTF over the target surface from a given BTF sample. Then, we let the user interactively paint BTF patches onto the surface such that the painted patches seamlessly integrate with the background patterns. Our system is based on a patch-based texture synthesis approach known as quilting. We present a graphcut algorithm for BTF synthesis on surfaces and the algorithm works well for a wide variety of BTF samples, including those which present problems for existing algorithms. We also describe a graphcut texture painting algorithm for creating new surface imperfections (e.g., dirt, cracks, scratches) from existing imperfections found in input BTF samples. Using these algorithms, we can decorate surfaces with real-world textures that have spatially-variant reflectance, fine-scale geometry details, and surfaces imperfections. A particularly attractive feature of BTF painting is that it allows us to capture imperfections of real materials and paint them onto geometry models. We demonstrate the effectiveness of our system with examples.

We propose textural features, which are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture and no knowledge of illumination direction or spectrum. Hence, these features are suitable for content-based image retrieval (CBIR) of realistic scenes with colour textured objects and variable illumination. The illumination invariants are derived from Markov random field based texture representations. Our illumination invariant features are favourably compared with frequented features in this area - the local binary patterns, steerable pyramid and Gabor textural features, respectively. The superiority of our new invariant features is demonstrated in the illumination invariant recognition of the most advanced representation for realistic real-world materials - bidirectional texture function (BTF) textures.

Efficient and realistic rendering of cloth is of great interest especially in the context of e-commerce. Aside from the simulation of cloth draping, the rendering has to provide the look and feel of the fabric itself. In this paper we present a novel interactive rendering algorithm to preserve this look and feel of different fabrics. This is done by using the bidirectional texture function (BTF) of the fabric, which is acquired from a rectangular probe and after synthesis, mapped onto the simulated geometry. Instead of fitting a special type of bidirectional reflection distribution function (BRDF) model to each texel of our BTF, we generate view-dependent texture-maps using a principal component analysis of the original data. These view-dependent texture maps are then illuminated and rendered using either point-light sources or high dynamic range environment maps by exploiting current graphics hardware. In both cases, self-shadowing caused by geometry is taken into account. For point light sources, we also present a novel method to generate smooth shadow boundaries on the geometry. Depending on the geometrical complexity and the sampling density of the environment map, the illumination can be changed interactively. To ensure interactive frame rates for denser samplings or more complex objects, we introduce a principal component based decomposition of the illumination of the geometry. The high quality of the results is demonstrated by several examples. The algorithm is also suitable for materials other than cloth, as far as these materials have a similar reflectance behavior.

Surface reflectance of real-world materials is now widely represented by the bidirectional reflectance distribution function (BRDF) and also by spatially varying representations such as SVBRDF and the bidirectional texture function (BTF). The raw surface reflectance measurements are typically compressed or fitted by analytical models, that always introduce a certain loss of accuracy. For its evaluation we need a distance function between a reference surface reflectance and its approximate version. Although some of the past techniques tried to reflect the perceptual sensitivity of human vision, they have neither optimized illumination and viewing conditions nor surface shape. In this paper, we suggest a new image-based methodology for comparing different anisotropic BRDFs. We use optimization techniques to generate a novel surface which has extensive coverage of incoming and outgoing light directions, while preserving its features and frequencies that are important for material appearance judgments. A single rendered image of such a surface along with simultaneously optimized lighting and viewing directions leads to the computation of a meaningful BRDF difference, by means of standard image difference predictors. A psychophysical experiments revealed that our surface provides richer information on material properties than the standard surfaces often used in computer graphics, e.g., sphere or blob.

Bidirectional texture function (BTF) is 7D function of planar coordinates, spectral coordinate, and viewing and illumination angles, respectively. BTF is the recent most advanced representation of visual properties of surface materials. Unlike smooth textures, it specifies their altering appearance due to varying illumination and viewing conditions. This BTF visual appearance dependency on viewing and illumination conditions significantly complicates not only its acquisition, representation, and modeling but also makes its rendering noticeably more demanding. BTF textures are acquired by costly measurements of real materials and their subsequent nontrivial processing. While several techniques for measurement or processing of BTF textures have been described already, there is no environment allowing to support BTF texture rendering. This contribution describes novel Blender texture plugin for the purpose of BTF texture mapping and rendering. The plugin benefits from our previously developed BTF Roller texture enlargement method which is integral part of its implementation. The presented plugin allows to create realistic computer animations with additional BTF textures of any required size mapped onto an object surfaces while the other functionality of Blender retains.

In pursuit of photorealistic rendering of surface material, Bidirectional Texture Function (BTF) has been used frequently in recent years. Its main drawback is its massive data size. To solve this, the Spatial Bidirectional Reflectance Function (SBRDF) techniques compress BTFs into reflectance model parameters. However, SBRDF cannot produce the self-shadowing and self-occlusion mesostructure effects in many real-world surfaces. Aiming at this drawback, we investigate how self-shadowing and self-occlusion affect the surface appearance by additional physically-based analysis. We mainly rely on two physical phenomena to separate self-shadowing and self-occlusion into two independent effects. First, the self-shadowing is view independent. Second, the self-occlusion is independent of changes in lighting direction. After those analyses, we are able to add self-shadowing and self-occlusion effects to SBRDF to achieve rendering quality that is much closer to the original uncompressed BTF data than SBRDF.

The subject of the paper is to discuss and quantify deviations from reciprocity of the bidirectional reflectance distribution function (BRDF), i.e., the difference of BRDF obtained when inverting illumination and viewing directions. Directional reciprocity is not valid in general, because when the illumination beam has a spatial extension larger than the viewed area (as is most often the case for BRDF measurements), some of the scatterers building up the observed radiance are located at different places in reciprocal measurements. The physical systems under consideration in the two experiments are different, hence the breakdown of reciprocity. The paper develops a theory aiming at a quantitative estimation of deviations from directional reciprocity due to this factor. The theory is based on integral forms of the radiative transfer equation in a horizontal slab of heterogeneous absorbing and scattering media. The observed scene radiance is expanded in a series of scattering orders. Integral expressions of the single‐ and multiple‐scattering radiance are derived and put in a form suitable for the analysis of the reciprocity problem. The first‐order expression leads to an estimate of the order of magnitude ε of the relative deviations from reciprocity, , where D is the size of the viewed area (pixel size for imaging sensors), h is the vertical photon mean free path, δQ/Q is a measure of the scene heterogeneity, and θi, θv, and ϕ are the illumination and view zenith angles and the relative azimuth between illumination and view directions. It is argued that this order of magnitude should remain approximately valid if all orders of scattering are taken into account. A discussion of practical applications in various fields, laboratory optical reflectometry, Earth radiation budget monitoring, and terrestrial surfaces remote sensing is given.

Commonly, experimental data on surface directional reflectance are not properly corrected for atmospheric effects. In this paper, we describe a new method for rigorous retrieval of the bidirectional reflectance distribution function (BRDF) from ground‐based measurements. It obtains the pointwise BRDF in the view directions and the best fit parameters of the approximating analytical model. Unlike previously developed algorithms, it can perform a retrieval using directional observations made at a single solar angle. This improvement allows one to process experiments with incomplete sets of measurements, such as those contaminated by clouds. The paper describes the performance of the method and its sensitivity to atmospheric parameters. Using rigorous direct modeling of the reflected radiance and developed inversion algorithm, we performed an analysis of BRDF errors, typical for measurements. It shows that the BRDF shape distortions due to diffuse irradiance are considerable in the visible and near‐IR, even for low aerosol content in the atmosphere. This result confirms that an accurate atmospheric correction should be a required processing step in the experimental research of anisotropic surface reflectance.

Measured material representations like Bidirectional Texture Functions or Reflectance Fields offer very realistic appearance but the user is currently not capable of changing this appearance in an effective and intuitive way. Such editing operations would require a low-dimensional but expressive model for appearance that exposes only a small set of intuitively editable parameters (1D-sliders, 2D-maps) to the user but preserves all visually relevant details. In this paper we present a novel editing technique for complex spatially varying materials. It is based on the observation that we are already good in modeling the basic geometric structure of many natural and manmade materials but still have not found effective models for the detailed small-scale geometry and the interaction of light with these materials. Our main idea is to use procedural geometry to define the basic structure of a material and then to enrich this structure with the BTF information captured from real materials. By employing recent algorithms for real-time texture synthesis and BTF compression our technique allows interactive editing.

The diffuse and specular components of leaf reflection are both important to determine the leaf optical properties as well as to describe the leaf bidirectional reflectance distribution function (BRDF). However, the specular component is usually ignored in practice in numerous canopy reflectance models that describe the interaction between solar light and vegetated scene components. To evaluate the impact of leaf-specular reflection on canopy bidirectional reflectance factor (BRF) characteristics, we introduce a leaf BRDF model into the radiosity-graphics combined model (RGM; a 3-D scene model) to calculate canopy BRFs with nondiffuse leaves. The modified RGM is validated by comparing simulated BRFs against in situ measured BRFs over real maize canopies. The results show that ignorance of leaf-specular reflection can result in up to 50% of relative error in the blue band (435.8 nm). A series of maize canopies with different leaf angle distributions (LADs) is reconstructed to investigate the effect of five major biophysical/geometrical parameters such as leaf area index, LAD, leaf surface property, view direction, and solar zenith angle on leaf-specular reflection contributions to the canopy BRF. It is demonstrated that increasing the incident solar zenith angle and decreasing the mean leaf angle impact the angular distribution of the canopy BRF more significantly than other factors. The cumulative hemispherical relative and absolute errors of canopy BRF caused by the leaf-specular reflection are often too large to be ignored, even for canopies with rough surface leaves. Moreover, the relative error of BRF in visible waveband shows that, in general, leaf-specular reflection has a large impact than that in near-infrared waveband. However, such impact can be sufficiently accounted for by even just consideration of the first-order leaf-specular reflection in canopy reflectance calculation, leading to a substantial improvement in simulation accuracy for most vegetation canopies.

The forest canopy vertical structure, understory spatial distribution as well as bare soil ground under a forest canopy strongly affect the accuracy of retrieving leaf area index (LAI) using optical remotely sensed data. Combining the reflectance from two different view directions and geometric optical (GO) radiative model, we investigated the effects of background information on retrieving forest canopy LAI using moderate resolution data for temperate forest in Northeastern China. Firstly, the forest background reflectance (BR) was computed using the bidirectional reflectance distribution function (BRDF) product from MODIS data. Then the forest canopy effective leaf area index (LAIe) was retrieved using the four scale geometric optical radiative model after removing the effects of forest background. It was found that the LAIe estimates without considering and with considering forest background contribution can explain 46 % and 36 % variations of field measurement-based LAIe (p<; 0.01, N=28), respectively. The forest canopy LAIe estimation without removing background influence can result in the LAIe overestimation ranging from 20 % to 46 %, thus it is necessary to separate the contribution of forest background to total forest canopy reflectance.