Calculating the reflectance map (original) (raw)
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Reflectance and texture of real-world surfaces
ACM Transactions on Graphics, 1999
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 v...
Analyse de l'illumination et des propriétés de réflectance en utilisant des collections d'images
Http Www Theses Fr, 2011
The main objective of this thesis is to exploit the photometric information available in large photo collections of outdoor scenes to infer characteristics of the illumination, the objects and the cameras. To achieve this goal two problems are addressed. In a preliminary work, we explore optimal representations for the sky and compare images based on its appearance. Much of the information perceived in outdoor scenes is due to the illumination coming from the sky. The solar beams are reflected and refracted in the atmosphere, creating a global illumination ambience. In turn, this environment determines the way that we perceive objects in the real world. Given the importance of the sky as an illumination source, we formulate a generic 3-step process in order to compare images based on its appearance. These three stages are: segmentation, modeling and comparing of the sky pixels. Different approaches are adopted for the modeling and comparing phases. Performance of the algorithms is validated by finding similar images in large photo collections. A second part of the thesis aims to exploit additional geometric information in order to deduce the photometric characteristics of the scene. From a 3D structure recovered using available multi-view stereo methods, we trace back the image formation process and estimate the models for the components involved on it. Since photo collections are usually acquired with different cameras, our formulation emphasizes the estimation of the radiometric calibration for all the cameras at the same time, using a strong prior on the possible space of camera response functions. Then, in a joint estimation framework, we also propose a robust computation of the global illumination for each image, the surface albedo for the 3D structure and the radiometric calibration for all the cameras.
Linear light source reflectometry
2003
Abstract This paper presents a technique for estimating the spatially-varying reflectance properties of a surface based on its appearance during a single pass of a linear light source. By using a linear light rather than a point light source as the illuminant, we are able to reliably observe and estimate the diffuse color, specular color, and specular roughness of each point of the surface.
Spectral Gradient: A Surface Reflectance Measurement Invariant to Geometry and Incident Illumination
1999
Although photometric data is a readily available dense source of information in intensity images, it is not widely used in computer vision. A major drawback is its dependence on viewpoint and incident illumination. A novel methodology is presented which extracts reflectivity information of the various materials in the scene independent of incident light and scene geometry. A scene is captured under three different narrow-band color filters and the spectral derivatives of the scene are computed. The resulting spectral derivatives form a spectral gradient at each pixel. This spectral gradient is a surface reflectance descriptor which is invariant to scene geometry and incident illumination for smooth diffuse surfaces. The invariant properties of the spectral gradients make them a particularly appealing tool in many diverse areas of computer vision such as color constancy, tracking, scene classification, material classification, stereo correspondence, even re-illumination of a scene.
Image statistics for surface reflectance perception
Journal of the Optical Society of America A, 2008
Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.
Recovery of Surface Reflectances Using Video Camera Image Signals under Unknown Illuminations
Optical Review, 1997
Estimation of surface spectral reflectance functions and colorimetric values 0L object colors was carried out for the irnage data captured by video camera under unknown illuminations. The estimation method is based on the finite-dimensional linear model of illuminants and surfaces using a single reference reflectance with known surLace spectral reflectance in a scene. Experimental results showed that recovered surface spectral refiectance functions are the almost same for different illuminations. This method is useful for the colorimetric calibration 0L the devices, since any set of orthonormal basis vectors to represent illuminations and any set of eigen vectors derived Lrom principal component analysis on the data set of a color chart to express surfaces of different objects can be applied to the estimation. The recovered surface reflectances were evaluated by color differences in CIE L*a*b* color space.
Acquiring and Using Realistic Reflectance Data in Computer Graphics Images
Analytical models of light reflection are in common use in computer graphics. However, as the sophistication of rendering methods has increased, analytical models have become less adequate for generating images. Reflectance data obtained by empirically measuring real world surfaces is needed to create more realistic looking images. In this paper we examine several issues relevant to using measured reflectance functions in generating computer graphics images. We give an overview of the techniques involved in measuring and tabulating reflectance data. We compare and contrast measured reflectance functions with analytical illumination models, and evaluate several methods for interpolating tabulated reflectance functions. We also highlight potential areas of future research. 1 Introduction The most fundamental operation in rendering computer graphics images is the computation of how light reflects off surfaces. This computation is often performed using a local illumination model. This i...
Color Research & Application, 2015
A spectral-based method can acquire and represent the surface appearance of a given material physically correctly. But, it has drawbacks due to its high measurement cost and a long computation time in measuring, modeling, and rendering. In this article, we present spectral recovery and representation of spectral bidirectional reflectance distribution function (BRDF) from multispectral reflectance measurements in which we can render real appearance materials over a 3D model with accuracy and efficiency. First of all, an accurate spectral BRDF recovery algorithm, which transforms multispectral high dynamic range images into highly dense BRDFs in both a spectral and an angular domain, is proposed. Second, an efficient representation method is developed representing spectral BRDFs compactly using a factorization method and an adaptive spectral sampling method that uses a given error bound. The results show that the proposed method can compress the spectral BRDF data down by several hundred times while maintaining the given accuracy in colorimetric and spectral domains under a specific illuminant.
Reflectance Analysis for 3D Computer Graphics Model Generation
Graphical Models and Image Processing, 1996
suming and can be a bottle neck for realistic image syn-For synthesizing realistic images of a real three dimensional thesis. Therefore, techniques to obtain object models object, reflectance properties of the object surface, as well as automatically by observing a real object could have a great the object shape, need to be measured. This paper describes impact in practical applications. one approach to create a three dimensional object model with Techniques for measuring the geometric information by physically correct reflectance properties by observing a real using range data from real objects have received much object. The approach consists of three steps. First, a sequence attention recently. Turk and Levoy developed a system of range images and color images is measured by rotating a which can merge multiple surface meshes one by one, using real object on a rotary table with fixed viewing and illumination two step strategy: registration by the iterative closest-point directions. Then, the object shape is obtained as a collection algorithm (ICP algorithm) and integration by the zippering of triangular patches by merging multiple range images. Second, by using the recovered object shape, color pixel intensities algorithm [23]. Higuchi et al. have developed a method of the color image sequence are mapped to the object surface for merging multiple range views of a free-form surface and separated into the diffuse and specular reflection compoobtained from arbitrary viewing directions, with no initial nents. Finally, the separated reflection components are used to estimation of relative transformation among those viewing estimate parameters of the Lambertian reflection model and a directions [6]. The method is based on the spherical attrisimplified Torrance-Sparrow reflection model. We have sucbute image (SAI) representation of free-form surfaces cessfully tested our approach using images of a real object. which was originally introduced by Delingette et al. in [4]. Synthesized images of the object under arbitrary illumination Hoppe et al. [7] have introduced an algorithm to construct conditions are shown in this paper.
Component estimation of surface spectral reflectance
1990
For inhomogeneous materials, the standard reflectance model suggests that under all viewing geometries surface reflectance functions can be described as the sum of a constant function of wavelength (specular) and a diffuse function that is characteristic of the material. As the viewing geometry varies, the relative contribution of these two terms varies. In a previous study [J. Opt. Soc. Am. A 6,576 (1989)] we described how to use light reflected from inhomogeneous materials, measured in different viewing geometries, to estimate the relative spectral power distribution of the ambient light. Here we show that two restrictions, that (a) surface reflectance functions are all nonnegative and (b) surface reflectance functions are the positive weighted sum of subsurface (diffuse) and interface (specular) components, may be used to estimate the subsurface component of the surface reflectance function. A band of surface spectral reflectances is recovered, as possible solutions for the subsurface estimates.