We consider the rendering of diffuse objects under distant illumination, as specified by an environment map. Using an analytic expression for the irradiance in terms of spherical harmonic coefficients of the lighting, we show that one needs to compute and use only 9 coefficients, corresponding to the lowest-frequency modes of the illumination, in order to achieve average errors of only 1%. In other words, the irradiance is insensitive to high frequencies in the lighting, and is well approximated using only 9 parameters. In fact, we show that the irradiance can be procedurally represented simply as a quadratic polynomial in the cartesian components of the surface normal, and give explicit formulae. These observations lead to a simple and efficient procedural rendering algorithm amenable to hardware implementation, a prefiltering method up to three orders of magnitude faster than previous techniques, and new representations for lighting design and image-based rendering.

In this paper we present two novel reflectance measurement procedures that require fewer total measurements than standard uniform sampling approaches. First, we acquire densely sampled reflectance data for a large collection of different materials. Using these densely sampled measurements we analyze the general surface reflectance function to determine the local signal variation at each point in the function’s domain. We then use wavelet analysis to derive a common basis for all of the acquired reflectance functions as well as a corresponding non-uniform sampling pattern that corresponds to all non-zero wavelet coefficients. Second, we show that the reflectance of an arbitrary material can be represented as a linear combination of the surface reflectance functions. Furthermore, our analysis provides a reduced set of sampling points that permits us to robustly estimate the coefficients of this linear combination. These procedures dramatically shorten the acquisition time for isotropic reflectance measurements. We present a detailed description and analysis of our measurement approaches and sampling strategies.

We describe the basis of the work he have currently under way to implement a new rendering algorithm called light-driven global illumination. This algorithm is a departure from conventional raytracing and radiosity renderers which addresses a number of deficiencies intrinsic to those approaches. 1 Introduction In computer graphics, we use illumination -- the study of how light interacts with matter to produce visible scenes -- to produce realistic images. Illumination encompasses both local and global phenomena. Local illumination describes the interaction of light with a single, small volume or surface element with given incident and viewing directions. We take the fundamental equation describing local illumination to be L = L e + Z \Omega R N f r (S 0 ; V)L i jN \Delta S 0 j d! 0 i + Z \Omega T N f t (S 0 ; V)L i jN \Delta S 0 j d! 0 i (1) where N is the surface normal, L is the total radiance given off (either L r , reflected, or L t , transmitted) in direct...

. There has been great success in speeding up global illumination computation in diffuse environments. The concept of clustering allows radiosity computations even for scenes of high complexity. However, for lighting simulations in complex non-diffuse scenes, Monte-Carlo sampling methods are currently the first choice, because non-diffuse finite-element approaches still exhibit enormous computation times and are thus only applicable to scenes of very modest complexity. In this paper we present a novel clustering approach for radiance computations, by which we overcome some of the problems of previous methods. The algorithm computes a radiance solution within a line space hierarchy, that allows us to efficiently represent light propagation and reflection between arbitrary non-diffuse surfaces and clusters. 1 Introduction 1.1 Rendering Equation All global illumination algorithms compute an approximate solution of the rendering equation [Kaj86]. In this equation, a scene is assumed to ...

Analytical models of light reflection are in common use in computer graphics. However, models based on measured reflectance data promise increased realism by making it possible to simulate many more types of surfaces to a greater level of accuracy than with analytical models. They also require less expert knowledge about the illumination models and their parameters. There are a number of hurdles to using measured reflectance functions, however. The data sets are very large. A reflectance distribution function sampled at five degrees angular resolution, arguably sparse enough to miss highlights and other high frequency effects, can easily require over a million samples, which in turn amount to over 4 megabytes of data. These data then also require some form of interpolation and filtering to be usedeffectively. In this paper we examine a wavelet basis representation of reflectance functions. 1 Introduction One of the goals of image synthesis is to produce images of three dimensional com...

Physically-based rendering methods represent the core of current realistic image synthesis frameworks. These methods, through a plausible simulation of the processes of light propagation and interaction with objects, have contributed considerably to the improvement of photorealistic rendering. The state of art research in this area includes the simulation of natural phenomena and the incorporation of biological aspects affecting light propagation in natural environments. The search for more efficient rendering solutions is also of major interest for the rendering community. In this dissertation biologically and physically-based models for light interaction with plant leaves are presented. Moreover, since the light that reach a plant leaf may be propagated directly from a light source or indirectly, due to multiple interactions with other objects in the environment, global illumination issues are also addressed, more specifically related to the radiosity method. This method is commonly...