Lambertian Model Research Articles

Universities and Industry: Does the Lambert Code of Governance Meet the Requirements of Good Governance?

AbstractThe Lambert Model Code of Governance proposes to institutionalise the dominance of governors from commercial and industrial organisations as core members of compact and effective boards controlling UK universities. It is the latest expression of a fashion for viewing university governance as an overly‐simple example of an obsolete system, where overweening and obstructive committee systems inhibit universities from achieving more significant and business‐relevant activity. In this paper university governance is analysed in terms of classic agency analysis, in the Jensen and Meckling tradition. This suggests that governance of and in the system is complex and that, although inherited structures may indeed be deficient, the prescription of the Lambert Review is profoundly flawed and would be unlikely to achieve improvement in UK universities’ competitiveness or attainment of mission.

Estimation of the luminance map for a Lambertian photometric model: application to the study of road surface roughness

The study of rough textured surfaces such as road coverings, is generally made on gray-level images. This supposes that the variations of gray levels are representative of the local variations of the relief. This assumption is justified, in the case of surfaces that are uniformly colored, but finds its limit in the case when these surfaces present variations of color or aspect. The corresponding image then presents variations of gray levels that can be related to the color variations or to the relief variations or both. It becomes difficult in this case to work out the criteria of roughness based on image analysis. It is then necessary to develop, before any study of roughness, an estimation of the luminance map linked to color variations. To do that, we have linked the gray-level value to the height variation of the road-covering surface. Thus, we express the luminance distribution according to these height variations, obtained through a laser sensor, and to the image gray level. This method enables us to compute the distribution of the luminance map. We characterize this distribution by considering statistical parameters of its histogram. Then we test the effectiveness of our approach by comparing the evolution of the criterion of roughness on road surfaces, first without considering the luminance distribution and then by taking it into account. The results obtained show that this approach leads to a good discrimination by the criterion of roughness in the case of colored surfaces.

Shape and texture preserved non‐photorealistic rendering

AbstractTwo approaches, image‐space and object‐space, exist for non‐photorealistic rendering (NPR). The object‐space approach has an advantage that it is able to access the 3D shape information of the scene with a 3D model. In this paper, we present a non‐stroke based image‐space technique that has the strength similar to that of the object‐space approach, but without involving explicit 3D models. The basic idea is to factorise the Lambertian model to obtain the shape and texture information implicitly contained in the image. We also develop a specific anisotropic low‐pass image filter, which can smooth an image without blurring important features. With the developed techniques, we present two NPR styles, the sketching style and the painting style. Although our work does not aim to mimic any specific existing art form, the sketching style can generate effects similar to those of the pen‐and‐ink and the painting style is able to produce the colour permeating effects of watercolour. Copyright © 2004 John Wiley & Sons, Ltd.

Recovery of shape and surface reflectance of specular object from relative rotation of light source

In this paper, we present a method for recovery of shape and surface reflectance of specular object from color images taken with a rotating light source.The image sequence is taken with a fixed camera while the light source is relatively rotating around the axis parallel to the optical axis of the camera. By assuming Lambertian reflectance model for the object surface and the orthographic projection for the camera, we can derive a simple relationship between the body reflectance at every object surface point and the rotating angle of the light source.For adapting specular reflectance that can be represented by Phong's model,we develop the algorithm to extract only body reflectance component which obeys the simple relationship for estimating surface normals and body reflectance component. As a result,the object shape and body reflectance distribution of the object surface can be recovered. In addition to this, reflectance parameters of specularity are also estimated by minimize the fitting error of the specular reflectance model.For demonstrating the effectiveness of the proposed method, we show the shape, body reflectance, and specular reflectance of specular objects, which are successfully recovered by the proposed method.

Leaf area index inferred from solar beam transmission in mixed conifer forests on complex terrain

Forest process models are used to predict forest growth in a broad range of conditions. Because more than a quarter of the world’s forests are in mountainous regions, leaf area index (LAI) must frequently be estimated for forests in complex terrain. LAI is often inferred from canopy light transmission using various canopy models. Choice of a canopy model becomes especially problematic in complex terrain because the complex topography changes the path length of the solar beam through the canopy. For example, if solar elevations are expressed relative to the inclined surface, low elevations can occur on steep slopes at any time of the day, especially on surfaces facing north (in the northern hemisphere). We inferred LAI with various models at 36 plots in a mixed conifer forest in northern Idaho, USA, over a wide range of altitude and solar insolation. We compared these inferences to allometric estimates of LAI. We also tested a theoretical solution for path length on complex terrain. We conclude that the use of this path length correction does not improve agreement between ceptometer LAI and allometric LAI. However, residuals of the fit between transmission and allometric LAI were weakly related to path length ( P=0.052) and squared path length ( P=0.049) in a quadratic multiple linear regression. The best fits between ceptometer LAI and allometric LAI were both based on extinction coefficients corrected only for solar zenith angle; we recommend the Beer–Lambert model for its simplicity. We analyzed residuals of ceptometer estimates of LAI and determined that they were correlated with species composition. These results suggest that species composition might be used to predict extinction coefficients, though the current data set will not support such prediction. Thus, terrain complexity had only a minor influence on model predictions of leaf area index in these stands, simplifying the prediction of LAI in mountain forests.

Incorporating illumination constraints in deformable models for shape from shading and light direction estimation

We present a method for the integration of nonlinear holonomic constraints in deformable models and its application to the problems of shape and illuminant direction estimation from shading. Experimental results demonstrate that our method performs better than previous Shape from Shading algorithms applied to images of Lambertian objects under known illumination. It is also more general as it can be applied to non-Lambertian surfaces and it does not require knowledge of the illuminant direction. In this paper, (1) we first develop a theory for the numerically robust integration of nonlinear holonomic constraints within a deformable model framework. In this formulation, we use Lagrange multipliers and a Baumgarte stabilization approach (1972). (2) We also describe a fast new method for the computation of constraint based forces, in the case of high numbers of local parameters. (3) We demonstrate how any type of illumination constraint, from the simple Lambertian model to more complex highly nonlinear models can be incorporated in a deformable model framework. (4) We extend our method to work when the direction of the light source is not known. We couple our shape estimation method with a method for light estimation, in an iterative process, where improved shape estimation results in improved light estimation and vice versa. (5) We perform a series of experiments.

Color constancy from physical principles

A well known property of human vision, known as color constancy, is the ability to correct for color deviations caused by a difference in illumination. A common approach to investigate color constant behavior is by psychophysical experiments, regarding the human visual system as a black box responding to a well defined change in an laboratory setup.A fundamental problem in psychophysical experiments is that significant conclusions are hard to draw due to the complex experimental environment necessary to examine color constancy. An alternative approach to reveal the mechanisms involved in color constancy is by modeling the physical process of spectral image formation. In this paper, we aim at a physical basis for color constancy rather than a psychophysical one.By considering spatial and spectral derivatives of the Lambertian image formation model, object reflectance properties are derived independent of the spectral energy distribution of the illuminant. Gaussian spectral and spatial probes are used to estimate the proposed differential invariant. Knowledge about the spectral power distribution of the illuminant is not required for the proposed invariant.The physical approach to color constancy offered in the paper confirms relational color constancy as a first step in color constant vision systems. Hence, low-level mechanisms such as color constant edge detection may play an important role in front-end vision. The research presented raises the question of whether the illuminant is estimated at all in pre-attentive vision.

Room acoustics auralization studies of laterally incident boss-model scattering

Computation of room impulse responses by commercial auralization programs typically employs simplified Lambert models to account for nonspecular scattering. However, Lambert scattering models, developed primarily for diffuse lighting computation, have limited validity in acoustics. Instead, in this study, surface scattering from hemispherical bosses on walls is computed with numerical models based on exact classical solutions. Scattering impulse responses for auralization are calculated with various configurations of bosses on infinite planes on both sides of a binaural receiver (approximately 7–10 m away). The physical sound field is analyzed along with the resulting subjective effects of varying boss size and scatterer density.

Reflection model for calculation of the impulse response on IR‐wireless indoor channels using ray‐tracing algorithm

AbstractThis paper presents a simulation tool for the fast calculation of the impulse response on infrared (IR) wireless indoor channels. We used Phong's model to approximate the reflection pattern of the indoor surfaces upon which a Monte Carlo ray‐tracing method allows us to evaluate the impulse response. We also present computer simulation results showing that the use of Phong's model can lead to differences with respect to Lambert's model in the evaluation of the impulse response when surfaces present a high specular component. © 2002 John Wiley & Sons, Inc. Microwave Opt Technol Lett 32: 296–300, 2002.

High-fidelity image reproduction using angular distribution of reflected spectral intensity

A method to reproduce images of an object under various observation conditions is presented. In this method, a series of multispectral images is captured by rotating the object under a point light source of which spectral power distribution and the position are known. The captured images are decomposed into diffuse and specular reflection component images based on the dichromatic reflection and the Lambertian models. Next, the incident angle of the illumination light and the angle between viewing direction and regular reflection are calculated based on observation geometry. Finally, the image under observation geometry is synthesized using the light-ray rearrangement technique. The experiments are carried out using two-dimensional objects, leather and fabric. Most of the synthesized images are shown to be the same as the images actually captured under the assumed illumination geometry, even if the object has complex reflection like fabric for which it is difficult to apply the reflection model used in computer graphics.

Enhanced 3D shape recovery using the neural-based hybrid reflectance model.

It is known that most real surfaces usually are neither perfectly Lambertian model nor ideally specular model; rather, they are formed by the hybrid structure of these two models. This hybrid reflectance model still suffers from the noise, strong specular, and unknown reflectivity conditions. In this article, these limitations are addressed, and a new neural-based hybrid reflectance model is proposed. The goal of this method is to optimize a proper reflectance model by learning the weight and parameters of the hybrid structure of feedforward neural networks and radial basis function networks and to recover the 3D object shape by the shape from shading technique with this resulting model. Experimental results, including synthetic and real images, were performed to demonstrate the performance of the proposed reflectance model in the case of different specular effects and noise environments.

A fast, accurate algorithm to account for non‐Lambertian surface effects on TOA radiance

Surface bidirectional reflectance distribution function (BRDF) influences both the radiance just above the surface and that emerging from the top of the atmosphere (TOA). In this study we propose a new, fast, and accurate algorithm CASBIR (correction for anisotropic surface bidirectional reflection) to account for such influences on TOA radiance. This new algorithm is based on four‐stream theory that separates the radiation field into direct and diffuse components in both upwelling and downwelling directions. Such a separation is important because the direct component accounts for a substantial portion of incident radiation under a clear sky, and the BRDF effect is strongest in the reflection of the incident direct radiation. The model is validated by comparison with a full‐scale, vector radiative transfer model for the atmosphere‐surface system [Ahmad and Fraser, 1982] for wavelengths from UV to near‐IR over three typical but very different surface types. The result demonstrates that CASBIR is accurate for all solar and viewing zenith and azimuth angles considered, with overall relative difference of less than 0.7%. Application of this algorithm includes both accounting for non‐Lambertian surface scattering on the emergent radiation above TOA and developing a more effective approach for surface BRDF retrieval from satellite‐measured radiance. Comparison with the result from the Lambertian model indicates that surface BRDF influence on TOA radiance is both angle and wavelength dependent. It increases as solar zenith angle decreases or wavelength increases and becomes strongest in the view directions where the surface reflection is most anisotropic (such as in the hot spot or Sun glint regions).

Deformation detection on composite reflectance surfaces using two-image photometric stereo

We present a new two-image photometric stereo method that is capable of determining surface deformations when extended light sources are used and the imager and light sources are close to the surface. Surface reflectance is modeled using a linear combination of Lambertian, backscatter, and new extended-source Phong specular reflection component models. The ambiguity resulting from using only two light sources is resolved in the surface normal integration phase, in which the resulting surface is constrained to being a valid image-based triangular facet surface. The method has been tested on an application involving waste-storage drum inspection and yields good accuracy.

Neural computation approach for developing a 3D shape reconstruction model

The shape from shading problem refers to the well-known fact that most real images usually contain specular components and are affected by unknown reflectivity. In this paper, these limitations are addressed and a new neural-based 3D shape reconstruction model is proposed. The idea behind this approach is to optimize a proper reflectance model by learning the parameters of the proposed neural reflectance model. In order to do this, new neural-based reflectance models are presented. The feedforward neural network (FNN) model is able to generalize the diffuse term, while the RBF model is able to generalize the specular term. A hybrid structure of FNN-based and RBF-based models is also presented because most real surfaces are usually neither Lambertian models nor ideally specular models. Experimental results, including synthetic and real images, are presented to demonstrate the performance of our approach given different specular effects, unknown illuminate conditions, and different noise environments.

Brightness temperatures of the lunar surface: Calibration and global analysis of the Clementine long‐wave infrared camera data

The scientific payload on the Clementine spacecraft included a long‐wave infrared (LWIR) camera with a single passband centered at a wavelength of 8.75 μm. The Clementine orbit deviated by ±30° from Sun synchronous, and for two lunar months, dayside nadir‐looking images were obtained near local noon. During the systematic mapping phase of the Clementine mission, approximately 220,000 thermal‐infrared images of the lunar surface were obtained. We have completed the calibration of the LWIR camera. Here we present the various steps involved in the calibration routine and the associated uncertainty analysis. The LWIR calibration routine can be outlined as follows: convert measured data number values to radiance via a calibration equation; subtract a zero‐flux background image from each lunar image; divide by a flatfield frame; identify bad pixels; smooth over only bad pixels; adjust radiances to reflect the absolute calibration; and convert radiances to brightness temperatures via the Planck function. Observed LWIR radiances can be converted to brightness temperatures, which provide information on various physical properties of the lunar surface. We also present here the LWIR global data set. The LWIR data from noontime orbits demonstrate that the Lambertian temperature model of cos1/4(i) is a fair approximation for nadir‐looking temperatures, rather than the cos1/6(i) behavior observed for ground‐based measurements of the full Moon. Deviations from the Lambertian model are likely due to surface roughness effects and variations in infrared emissivity. In addition, the LWIR global data set reveals the dayside lunar thermal emission to be largely governed by albedo and by the solar incidence angle.

A neural-learning-based reflectance model for 3-D shape reconstruction

In this letter, the limitation of the conventional Lambertian reflectance model is addressed and a new neural-based reflectance model is proposed of which the physical parameters of the reflectivity under different lighting conditions are interpreted by the neural network behavior of the nonlinear input-output mapping. The idea of this method is to optimize a proper reflectance model by a neural learning algorithm and to recover the object surface by a simple shape-from-shading (SFS) variational method with this neural-based model. A unified computational scheme is proposed to yield the best SFS solution. This SFS technique has become more robust for most objects, even when the lighting conditions are uncertain.

Corrections to "a new error function at hidden layers for fast training of multilayer perceptrons"

(e) (f) Fig. 6. Results for Lenna image: (a) the original Lenna image, (b) 3-D plot of the reconstructed surface by the proposed neural-based method, (c) 3-D plot of the reconstructed surface by the Lambertain model with the estimated light source direction by Zheng and Chellappa’s method, (d) 3-D plot of the reconstructed surface by the Lambertian model with incorrect light source direction, (e) 3-D plot of the reconstructed surface by the Torrance‐Sparrow model with the estimated light source direction by Zheng and Chellappa’s method, and (f) 3-D plot of the reconstructed surface by the Torrance‐Sparrow model with incorrect parameters setting.

Recovering cylindric and conic surfaces from contours and reflections

Cylindric and conic metallic parts are considered, which are subject to surface treatments (such as, e.g., lathe finishing or grinding) that make both Lambertian reflection models and purely specular ones inadequate. A new reflection model is introduced for such surface treatments, and a method is derived for the determination of the pose and the intrinsic geometric parameter of a cylindric surface or a conic one starting from a single view. This method uses both the projection of the outline of the surface and the reflection of known light sources onto it.

Explaining the differences between two previous meat generic advertising studies

United States producer organizations spend millions of dollars on generic advertising of both beef and pork and other promotion programs designed to stimulate consumers' demand for meat. Producers need to know if the money allocated to generic advertising and these promotion programs is effective in increasing the demand for meat. Past research disagreed about the effectiveness of meat generic advertising. Models of Ward and Lambert and Brester and Schroeder are reestimated and tested for misspecification. The Ward and Lambert Model is shown to be fragile. The statistically significant effect of advertising disappears with minor changes in the data and with a change in the sample period. [Econ-Lit citations: Q110, M370, C530] © 1999 John Wiley & Sons, Inc.

Land cover classification using Landsat TM imagery in the tropical highlands: The influence of anisotropic reflectance

Despite the tremendous attention given to conservation projects in the Neotropics, few published studies have documented remote sensing studies in tropical highland areas. Even fewer publications have addressed the use of topographic normalization methods in these regions. This article discusses the influence of anisotropic reflectance patterns on land cover classification for two study areas characterized by very rugged terrain and high relief. Landsat Thematic Mapper subscenes for sites in both Costa Rica and Ecuador were corrected using both Lambertian and non-Lambertian models. While use of the Lambertian model proved inappropriate for these mountainous areas, application of the non-Lambertian model enhanced classification accuracies.