Lambertian Model Research Articles

Color correction based on point clouds alignment in the logarithmic RGB space

Color distortion which is caused by different illuminations and different camera settings in imaging process, incurs many problems. To overcome these problems, color correction is required. In this paper, a novel method for point cloud alignment-based color correction is proposed to eliminate unwanted color variation between images of the same or similar scenes automatically. The method is based on the Lambertian reflection model. For the advantages inherent in the logarithmic representation of an image, we first project the RGB color space into the logarithmic color space; then, in the logarithmic color space, we prove that the point clouds of the same or similar objects in different images can be related by a 3D translation vector. Next, we seek to find an accurate translation vector to align corresponding point clouds; and finally, when the source image is transformed by the translation vector, it can exhibit a similar appearance to the reference image. Various experimental results verify the validity of the proposed algorithm.

ACT: A leaf BRDF model taking into account the azimuthal anisotropy of monocotyledonous leaf surface

Leaf reflectance of monocotyledons generally displays a strong azimuthal anisotropy due to the longitudinal orientation of the veins. The Cook and Torrance (CT) bidirectional reflectance distribution function model was adapted to account for this distinctive feature. The resulting ACT (Anisotropic Cook and Torrance) model is based on the decomposition of the roughness parameter into two perpendicular components. It is evaluated on sorghum (Sorghum halepense) and wheat (Triticum durum) leaf BRF (Bidirectional Reflectance Factor) measurements acquired using a conoscope system. Results show that the ACT model fits the measurements better than azimuthally isotropic surface models: the root mean square error computed over all the BRF measurements for both leaves decreases from ≈0.06 for the Lambertian model to ≈0.04 for the CT model and down to ≈0.03 for the ACT model. The adjusted value of the refraction index is plausible (n≈1.32) for both leaves while the retrieved roughness values perpendicular to the veins (sorghum=0.56; wheat=0.46) is about two times larger than that parallel to the veins (sorghum=0.27; wheat=0.18). Nonetheless, the observed residual discrepancies between the ACT model simulations and the measurements may be explained mainly by the Lambertian assumption of the volume scattering.

Illumination-insensitive texture discrimination based on illumination compensation and enhancement

As the appearance of a 3D surface texture is strongly dependent on the illumination direction, 3D surface-texture classification methods need to employ multiple training images captured under a variety of illumination conditions for each class. Texture images under different illumination conditions and directions still present a challenge for texture-image retrieval and classification. This paper proposes an efficient method for illumination-insensitive texture discrimination based on illumination compensation and enhancement. Features extracted from an illumination-compensated or -enhanced texture are insensitive to illumination variation; this can improve the performance for texture classification. The proposed scheme learns the average illumination-effect matrix for image representation under changing illumination so as to compensate or enhance images and to eliminate the effect of different and uneven illuminations while retaining the intrinsic properties of the surfaces. The advantage of our method is that the assumption of a single-point light source is not required, so it circumvents and overcomes the limitations of the Lambertian model and is also suitable for outdoor settings. We use a wide range of textures in the PhoTex database in our experiments to evaluate the performance of the proposed method. Experimental results demonstrate the effectiveness of our proposed methods.

Nondestructive Testing of the State of Surfaces Damaged by Corrosion Pitting

We study the problem of three-dimensional reconstruction of the surface on the basis of its two-dimensional images with an aim to apply the results of its solution for the analysis of the images of materials damaged by pitting. We propose a method for finding the depth of pitting according to the estimates of a series of metallographic images with the help of the Lambertian model of reflection of light. We determine the parameters of the model by analyzing the changes in the location of a source of light with the use of additional shading, and the invariable location of the receiver. The series of analyzed images contains a triple of images, obtained for different directions of illumination and also the shaded image of pitting. We describe a two-step algorithm aimed at the estimation of the characteristics of pitting on the surface of the material according to its images. In particular, we show that the use of the proposed methods enables one to obtain information about pittings. We also present an example of practical application of the developed algorithm for the 3D reconstruction of the surface of actual pitting.

Benthic effects on the polarization of light in shallow waters

Measurements of the upwelling polarized radiance in relatively shallow waters of varying depths and benthic conditions are compared to simulations, revealing the depolarizing nature of the seafloor. The simulations, executed with the software package RayXP, are solutions to the vector radiative transfer equation, which depends on the incident light field and three types of parameters: inherent optical properties, the scattering matrix, and the benthic reflectance. These were measured directly or calculated from measurements with additional assumptions. Specifically, the Lambertian model used to simulate benthic reflectances is something of a simplification of reality, but the bottoms used in this study are found to be crucial for accurate simulations of polarization. Comparisons of simulations with and without bottom contributions show that only the former corroborate measurements of the Stokes components and the degree of linear polarization (DoLP) collected by the polarimeter developed at the City College of New York. Because this polarimeter is multiangular and hyperspectral, errors can be computed point-wise over a large range of scattering angles and wavelengths. Trends also become apparent. DoLP is highly sensitive to the benthic reflectance and to the incident wavelength, peaking in the red band, but the angle of linear polarization is almost spectrally constant and independent of the bottom. These results can thus facilitate the detection of benthic materials as well as future studies of camouflage by benthic biota; to hide underwater successfully, animals must reflect light just as depolarized as that reflected by benthic materials.

A 3D Reconstruction Algorithm Based on PMS and Lambertian Model under Clear Water

A 3D Reconstruction Algorithm Based on PMS and Lambertian Model under Clear Water

Real-time three-dimensional fingerprint acquisition via a new photometric stereo means

A real-time means for three-dimensional (3-D) fingerprint acquisition is presented. The system is configured with only one camera and some white light-emitting diode lamps. The reconstruction is performed based on the principle of photometric stereo. In the algorithm, a two-layer Hanrahan–Krueger model is proposed to represent the finger surface reflectance property instead of the traditional Lambert model. By the proposed lighting direction calibration and the nonuniform lighting correction methods, surface normal at each image point can be accurately estimated by solving a nonlinear optimization problem. Finally, a linear normal transformation is implemented for the enhancement of 3-D models. The experiments are implemented with real finger and palm prints, and the results are also compared with traditional means to show its feasibility and improvement in the reconstruction accuracy.

Global photometric properties of Asteroid (4) Vesta observed with Dawn Framing Camera

Dawn spacecraft orbited Vesta for more than one year and collected a huge volume of multispectral, high-resolution data in the visible wavelengths with the Framing Camera. We present a detailed disk-integrated and disk-resolved photometric analysis using the Framing Camera images with the Minnaert model and the Hapke model, and report our results about the global photometric properties of Vesta. The photometric properties of Vesta show weak or no dependence on wavelengths, except for the albedo. At 554nm, the global average geometric albedo of Vesta is 0.38±0.04, and the Bond albedo range is 0.20±0.02. The bolometric Bond albedo is 0.18±0.01. The phase function of Vesta is similar to those of S-type asteroids. Vesta’s surface shows a single-peaked albedo distribution with a full-width-half-max ∼17% relative to the global average. This width is much smaller than the full range of albedos (from ∼0.55× to >2× global average) in localized bright and dark areas of a few tens of km in sizes, and is probably a consequence of significant regolith mixing on the global scale. Rheasilvia basin is ∼10% brighter than the global average. The phase reddening of Vesta measured from Dawn Framing Camera images is comparable or slightly stronger than that of Eros as measured by the Near Earth Asteroid Rendezvous mission, but weaker than previous measurements based on ground-based observations of Vesta and laboratory measurements of HED meteorites. The photometric behaviors of Vesta are best described by the Hapke model and the Akimov disk-function, when compared with the Minnaert model, Lommel–Seeliger model, and Lommel–Seeliger–Lambertian model. The traditional approach for photometric correction is validated for Vesta for >99% of its surface where reflectance is within ±30% of global average.

A sparse representation method for determining the optimal illumination directions in Photometric Stereo

The analysis of surface and texture details with the help of changes in illumination direction is a key task in 3D shape reconstruction either based on Photometric Stereo, Shape from Shading or Structured Light. This paper presents a novel approach for estimating the optimal illumination directions for the accurate calculation of the surface normals, while minimising the presence of shadows and the reconstructed albedo error. The method regards a sparse representation of the illumination arrangement and estimates the light directions using l1 optimisation. The Lambertian model is considered and the theoretical development is demonstrated with experimental results.

DEM Densification Using Perspective Shape From Shading Through Multispectral Imagery

Although photogrammetry has long been used as the primary method to produce digital elevation models (DEMs), there are still some locations that are not covered by multiangle images because of various limitations. Moreover, traditional interpolation methods for producing denser DEMs often cause oversmoothing, particularly over rough terrain. To formulate a robust procedure that is capable of reconstructing the terrain surface using sparse ground control points in heterogeneous areas, this letter describes an improved spatial enhancement method combining perspective shape from shading (SFS) using a single optical image. This method is called SFS-based densification using multispectral information (SDMI). First, the image irradiance equation based on the perspective Lambertian model is formulated as a static Hamilton–Jacobi equation and is solved using a fast sweeping strategy. We then reconstruct the relative surface shape and apply an edge-preserved iterative interpolation method to generate a higher resolution DEM grid. Multispectral information is used to reveal the actual surface reflection properties, and the land surface is classified into several types to better estimate surface reflectance. Experiments indicate that SDMI is effective for the interpolation of a sparse grid DEM over heterogeneous terrain.

Mars surface phase function constrained by orbital observations

The bidirectional photometric properties of the surface of Mars describe how remote measurements of surface reflectance can be linked to hemispherical albedo used for energy balance calculations. A simple Lambert's law is frequently assumed for global data processing, even though several local studies have revealed the complexity of Mars surface phase functions. In this paper, we derive a mean Bidirectional Reflectance Distribution Function (BRDF) representative of widespread typical Martian terrains. OMEGA and CRISM orbital observations are used to provide observational constraints at solar wavelengths over a wide range of viewing conditions all over the planet. Atmospheric contribution is quantified and removed using a radiative transfer model. We observe a common phase behavior consisting of a 5%–10% backscattering peak and, outside the backscattering region, a 10%–20% reflectance increase with emergence angles. Consequently, nadir measurements of surface reflectance typically underestimate hemispherical reflectance, or albedo, by 10%. We provide a parameterization of our mean Mars surface phase function based on Hapke formalism (ω=0.85, θ=17, c=0.6, b=0.12, B0=1 and h=0.05), and quantify the impact of the diffuse illumination conditions which change surface albedo as a function of local time and season. Our average phase function can be used as a refinement compared to the Lambertian surface model in global data processing and climate modeling.

Experimental study of image representation spaces in variational disparity calculation

Correspondence techniques start from the assumption, based on the Lambertian reflection model, that the apparent brightness of a surface is independent of the observer’s angle of view. From this, a grey value constancy assumption is derived, which states that a change in brightness of a particular image pixel is proportional to a change in its position. This constancy assumption can be extended directly for vector valued images, such as RGB. It is clear that the grey value constancy assumption does not hold for surfaces with a non-Lambertian behaviour and, therefore, the underlying image representation is crucial when using real image sequences under varying lighting conditions and noise from the imaging device. In order for the correspondence methods to produce good, temporally coherent results, properties such as robustness to noise, illumination invariance, and stability with respect to small geometrical deformations are all desired properties of the representation. In this article, we study how different image representation spaces complement each other and how the chosen representations benefit from the combination in terms of both robustness and accuracy. The model used for establishing the correspondences, based on the calculus of variations, is itself considered robust. However, we show that considerable improvements are possible, especially in the case of real image sequences, by using an appropriate image representation. We also show how optimum (or near optimum) parameters, related to each representation space, can be efficiently found.

SAR Imaging Simulation for Urban Structures Based on Analytical Models

In this letter, a novel synthetic aperture radar (SAR) imaging simulator is proposed based on analytical electromagnetic and geometric models for urban structures. The backscatter contributions are evaluated by an analytical electromagnetic model based on the Kirchhoff approach (KA) in either physics or geometrical optics approximations rather than specular and Lambertian models. In addition, the position vectors of object facets in the SAR imaging plane are evaluated by a closed-form analytical geometrical model based on the ray-tracing model. These models are expressed in terms of few and basic parameters. Compared with other numerical methods, they are helpful for improving the efficiency of the simulation, but more importantly, they are significant for direct understanding of and further interpreting the SAR image features. Some experiments validate the geometric and electromagnetic models and demonstrate the efficiency of the simulator.

Modelling inoculum dispersal and Sclerotinia stem rot gradients in canola fields

Dispersal of Sclerotinia sclerotiorum ascospores and sclerotinia stem rot (SSR) incidence were studied in commercial canola fields in two North Dakota locations from 2005 to 2007. Ascospores were collected on dishes containing a semi-selective medium that were placed on the soil, within plant canopies, at various distances from an area source of inoculum. SSR incidence was recorded at the end of the growing season. SSR incidence and inoculum gradients declined with distance from the area source in 2005 and 2007. In 2006, neither ascospores nor SSR were detected. The number of S. sclerotiorum colonies per dish (COL) declined between 30% and 75% within 40 m from the source, whereas SSR incidence declined by 50% within 12–17 m from the source. Ascospore dispersal and SSR gradients across years and locations were best described by Lambert's model (pseudo-R2 ≥ 0.98; P < 0.001) although the negative exponential model also provided a good fit for both (R2 ≥ 0.81; P ≤ 0.001). Every unit increase in the weekly mean COL represented an increase in SSR incidence that ranged between 0.5 and 0.75% (R2 = 0.96; P ≤ 0.0001) in 2005 and between 0.13 and 0.17% (R2 = 0.96; P ≤ 0.0001) in 2007. The existence of short distance dispersal, disease gradients, and the close association between inoculum concentration and disease incidence highlight the importance of within-field produced inoculum and provides support for the use of control tactics that emphasize reduction of sclerotia in canola fields as an effective way to reduce inoculum and control this disease.

Generalized 1D photopyroelectric technique for optical and thermal characterization of liquids

The analytical solution for the one-dimensional heat diffusion problem for a three-layer system, in the Beer–Lambert model for light absorption, is used for the implementation of a photopyroelectric (PPE) methodology for thermal and optical characterization of pigments in liquid solution, even for those ones potentially harmful to the pyroelectric sensor, taking the liquid sample's thickness as the only variable. Exponential decay of the PPE amplitude followed by a constant PPE phase for solutions at low pigment concentration, and exponential decay of the PPE amplitude but a linear decrease of the PPE phase for the concentrated ones are theoretically shown, allowing measurements of the optical absorption coefficient (at the wavelength used for the analysis) and the thermal diffusivity for the liquid sample, respectively. This PPE methodology was tested by measuring the thermal diffusivity of a concentrated solution of methylene blue in distilled water and the optical absorption coefficient, at two wavelengths (658 and 785 nm), of water solutions of copper sulfate at various concentrations. These optical parameters were used for measuring the molar absorption coefficient of this last pigment in water solution at these two wavelengths. This last optical property was also measured using a commercial spectrometer, finding very good agreement with the corresponding ones using this PPE technique.

The Partners for Change Outcome Management System (PCOMS): The Heart and Soul of Change Project.

Two continuous monitoring and feedback models have demonstrated gains in randomized clinical trials (RCTs): Lambert's Outcome Questionnaire (OQ) System and the Partners for Change Outcome Management System (PCOMS). This article chronicles the evolution of PCOMS from a simple way to discuss the benefit of services with clients to its emergence as an evidenced based practice to improve outcomes. Although based in Lambert's model, several differences are described: PCOMS is integrated into the ongoing psychotherapy process and includes a transparent discussion of the feedback with the client; PCOMS assesses the alliance every session; and the Outcome Rating Scale, rather than a list of symptoms rated on a Likert Scale, is a clinical tool as well as an outcome instrument that requires collaboration with clients. The research supporting the psychometrics of the measures and the PCOMS intervention is presented and the clinical process summarised. Examples of successful transportation to public behavioural health are offered and an implementation process that values consumer involvement, recovery, social justice, and the needs of the front-line clinician is discussed. With now nine RCTs and American Psychological Association endorsements to support it, it is argued that client-based outcome feedback offers a pragmatic way to transport research to practice. Keywords: client-based outcome feedback, patient-focused research, PCOMS, practice-based evidence The only man (sic) I know who behaves sensibly is my tailor; he takes my measurements anew each time he sees me. The rest go on with their old measurements and expect me to fit them. - George Bernard Shaw It is often reported that the average treated person is better off than approximately 80% of die untreated sample (Duncan, Miller, Wampold, & Hubble, 2010; Lambert & Ogles, 2004), which translates to an effect size (ES) of about 0.8. In short, the good news is that psychotherapy works. Unfortunately, Ulis is a bad, and ugly situation. The bad is twofold: First, dropouts are a significant problem in die delivery of mental healdi and substance abuse services, averaging at least 47% (Wierzbicki & Pekarik, 1993). Second, despite the fact that the general efficacy is consistently good, not everyone benefits. Hansen, Lambert, and Foreman (2002), using a national database of over 6,000 clients, reported a sobering picture of routine clinical care in which only 20% of clients improved compared with the 57%-67% rates typical of randomized clinical trials (RCTs). Whichever rate is accepted as more representative of actual practice, the fact remains that a substantial portion of clients go home without help. And the ugly: Perhaps explaining part of die wide range of results, variability among dierapists is me rule radier than the exception (Beuder et al., 2004). Some dierapists are simply much better man others. In a study of managed care treatment, for example, Wampold and Brown (2005) reported that 5% of outcome was attributable to therapist variability. In addition, dierapists overrate dieir effectiveness. Dew and Riemer (2003; reported in Sapyta, Riemer, & Bickman, 2005) asked 143 clinicians to rate dieir job performance from A+ to F. Two-tfiirds considered themselves A or better; not one dierapist rated him or herself as below average. So despite overall efficacy, dropouts are a substantial problem, many clients do not benefit, and dierapists vary significantly in outcomes and are poor judges of dieir effectiveness. A relatively new research paradigm called patient-focused research (Howard, Moras, Brill, Martinovich, & Lutz, 1996) addresses diese problems. Howard et al. (1996) advocated for die systematic evaluation of client response to treatment during die course of tiierapy and recommended diat such information be used to determine die appropriateness of die current treatment . . . [and] die need for further treatment . …

Carbon monoxide from shortwave infrared reflectance measurements: A new retrieval approach for clear sky and partially cloudy atmospheres

The GMES atmospheric services include global and European air quality monitoring and forecasting which require near real time delivery of atmospheric CO abundances. To achieve this, a numerically efficient retrieval approach for operational data processing is needed to derive CO column densities from shortwave infrared measurements in the 2.3μm band of the Sentinel 5 missions and its Precursor mission. The expected performance of both spectrometers will allow for clear-sky CO column retrievals over land with a precision of ≤10% and an overall accuracy of ≤15% even for background CO abundance and low surface reflection in the shortwave infrared spectral range. In this context, we present a new algorithm approach of the retrieval of CO from shortwave infrared measurements in clear sky and partially cloudy atmospheres over land and ocean surfaces. The algorithm employs simplified radiative transfer, where the model atmosphere is separated in a clear sky part, and a part which is bounded below by an elevated Lambertian reflector to account for atmospheric scattering by clouds and aerosols. Within the inversion scheme, Tikhonov regularization is used to determine, for each individual measurement, not only the vertically integrated CO column density and its retrieval error, but also the column averaging kernel. For the retrieval, a prior estimate of methane abundance is used to characterize the light path by retrieving effective cloud parameters from the shortwave infrared band itself. A performance analysis shows that, for a single cloud layer in the middle and lower troposphere, the bias on the CO retrieval due to the Lambertian cloud model is less than 2–3%. The effect of boundary layer aerosols can also be treated with similar accuracy. In contrast, the presence of elevated dust plumes above bright surfaces or a single layer cirrus cloud causes significant errors and, in these cases, a reasonably low retrieval bias can only be achieved for an optical depth in the shortwave infrared spectral range lower than 0.4. Another relevant error source for the CO retrieval algorithm is given by the prior uncertainty of methane. It is found that a 5% uncertainty in the methane column density causes biases of 3–9% on the retrieved CO column, depending on cloud fraction.

Application of neural network in integration of shape from shading and stereo

In this paper, a simple and efficient approach is presented for the reconstruction of 3-D surfaces using the integration of shape from shading (SfS) and stereo. First, a new SfS algorithm is derived to obtain the depth-map of a 3-D surface using linear and generalized Lambertian reflectance model. Later, the accuracy of the depth-map is improved by integrating stereo depth data. The stereo sparse depth data are obtained at the points which have higher similarity score in the rectified pair of stereo images. A feed-forward neural network is used to integrate the SfS and stereo depth data due to its strong nonlinear function approximation property. The integration process is based on the correction of 3-D visible surface obtained from SfS using the stereo data. The experiments have been performed on real and synthetic images to demonstrate the usability and accuracy of the approach.

Translational photometric alignment of single-view image sequences

Photometric stereo is a well-established method to estimate surface normals of an object. When coupled with depth-map estimation, it can be used to reconstruct an object’s height field. Typically, photometric stereo requires an image sequence of an object under the same viewpoint but with differing illumination directions. One crucial assumption of this configuration is perfect pixel correspondence across images in the sequence. While this assumption is often satisfied, certain setups are susceptible to translational errors or misalignments across images. Current methods to align image sequences were not designed specifically for single-view photometric stereo. Thus, they either struggle to account for changing illumination across images, require training sets, or are overly complex for these conditions. However, the unique nature of single-view photometric stereo allows one to model misaligned image sequences using the underlying image formation model and a set of translational shifts. This paper introduces such a technique, entitled translational photometric alignment, that employs the Lambertian model of image formation. This reduces the alignment problem to minimizing a nonlinear sum-squared error function in order to best reconcile the observed images with the generative model. Thus, the end goal of translational photometric alignment is not only to align image sequences, but also to produce the best surface-normal estimates given the observed images. Controlled experiments on the Yale Face Database B demonstrate the high accuracy of translational photometric alignment. The utility and benefits of the technique are further illustrated by additional experiments on image sequences suffering from uncontrolled real-world misalignments.

Managing maritime automobile terminals: an approach toward decision-support model for higher productivity

The article describes actions and strategies to obtain higher productivity on maritime automobile terminals. The main focus is on elaboration of efficient and effective organizational structure to model and implement short-term, mid-term and long-term strategies. In addition, with an empiric approach we combined the analyses of current findings in important scientific papers and our acknowledgments in practical research of north Adriatic maritime automobile terminals. The main goal is to propose actions towards increasing system's productivity. Based on our research of the north Adriatic maritime automobile terminals and with Lambert's model an in-deep analysis of limiting factors, user's expectations and possibilities for productivity increase has been performed. Moreover, with our acknowledgments a three-level decision-support model is presented. With an adequate model implementation it is possible to efficiently develop and implement different strategies of productivity measurement and productivity increase, especially in the fields of internal transport productivity, entrance/exit truck gates operations and wagon manipulations. According to our observation a significant increase might be achieved in all three fields.