A global illumination solution for general reflectance distributions

Sillion, Françis; Arvo, James; Westin, Stephen H.; Greenberg, Donald P.

doi:10.1145/127719.122739

Cited by 114 publications

(42 citation statements)

References 16 publications

(2 reference statements)

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“…Our use of spherical harmonics to represent the lighting is similar in some respects to previous methods such as that of Nimeroff et al [1994] that use steerable linear basis functions. Spherical harmonics have also been used before in computer graphics for representing BRDFs by a number of other authors [Sillion et al 1991;Westin et al 1992]. …”

Section: Frequency-space Representationsmentioning

confidence: 99%

A signal-processing framework for reflection

Ramamoorthi

Hanrahan

2004

ACM Trans. Graph.

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We present a signal-processing framework for analyzing the reflected light field from a homogeneous convex curved surface under distant illumination. This analysis is of theoretical interest in both graphics and vision and is also of practical importance in many computer graphics problems-for instance, in determining lighting distributions and bidirectional reflectance distribution functions (BRDFs), in rendering with environment maps, and in image-based rendering. It is well known that under our assumptions, the reflection operator behaves qualitatively like a convolution. In this paper, we formalize these notions, showing that the reflected light field can be thought of in a precise quantitative way as obtained by convolving the lighting and BRDF, i.e. by filtering the incident illumination using the BRDF. Mathematically, we are able to express the frequency-space coefficients of the reflected light field as a product of the spherical harmonic coefficients of the illumination and the BRDF. These results are of practical importance in determining the well-posedness and conditioning of problems in inverse rendering-estimation of BRDF and lighting parameters from real photographs. Furthermore, we are able to derive analytic formulae for the spherical harmonic coefficients of many common BRDF and lighting models. From this formal analysis, we are able to determine precise conditions under which estimation of BRDFs and lighting distributions are well posed and well-conditioned. Our mathematical analysis also has implications for forward rendering-especially the efficient rendering of objects under complex lighting conditions specified by environment maps. The results, especially the analytic formulae derived for Lambertian surfaces, are also relevant in computer vision in the areas of recognition, photometric stereo and structure from motion.

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Section: Frequency-space Representationsmentioning

confidence: 99%

A signal-processing framework for reflection

Ramamoorthi

Hanrahan

2004

ACM Trans. Graph.

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“…Even for a more simplified illumination design, the design of vision system hardware and software is still a complex process. Therefore, the use of image synthesis to evaluate vision system design and algorithm performance in part presentation applications is suggested as an effective tool to facilitate the analysis; examples of investigations using synthetic images are presented in [20][21][22][23][24][25][26][27][28]. In [29], Coulot presents numerical simulation as an effective method to determine optimal lighting for defect detection using machine vision.…”

Section: Proposed Approach and Prior Resultsmentioning

confidence: 99%

Efficient 3D characterization of raised topological defects in smooth specular coatings

Gnanaprakasam¹,

Parker

Ganapathiraman

et al. 2009

Image and Vision Computing

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“…To model the distance fall-off effect of a point source, we can multiply an attenuation factor that is related to the distance between and , given by (26) where is a user defined parameter. The overall relighting equation for a pixel with a point source at is given by (27) where s are the SRBF weights at pixel position . Let us denote the basis values as (28) We arrange the basis values in matrix form, denoted as .…”

Section: B Point Light Sourcementioning

confidence: 99%

An RBF-based compression method for image-based relighting

Leung

Wong

Lam

et al. 2006

IEEE Trans. on Image Process.

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In image-based relighting, a pixel is associated with a number of sampled radiance values. This paper presents a two-level compression method. In the first level, the plenoptic property of a pixel is approximated by a spherical radial basis function (SRBF) network. That means that the spherical plenoptic function of each pixel is represented by a number of SRBF weights. In the second level, we apply a wavelet-based method to compress these SRBF weights. To reduce the visual artifact due to quantization noise, we develop a constrained method for estimating the SRBF weights. Our proposed approach is superior to JPEG, JPEG2000, and MPEG. Compared with the spherical harmonics approach, our approach has a lower complexity, while the visual quality is comparable. The real-time rendering method for our SRBF representation is also discussed.

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A global illumination solution for general reflectance distributions

Cited by 114 publications

References 16 publications

A signal-processing framework for reflection

A signal-processing framework for reflection

Efficient 3D characterization of raised topological defects in smooth specular coatings

An RBF-based compression method for image-based relighting

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