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dc.contributor.authorSchröder, Peter
dc.contributor.authorGortler, Steven J.
dc.contributor.authorCohen, Michael F.
dc.contributor.authorHanrahan, Pat
dc.date.accessioned2014-10-21T07:30:15Z
dc.date.available2014-10-21T07:30:15Z
dc.date.issued1994en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/1467-8659.1320141en_US
dc.description.abstractOne important goal of image synthesis research is to accelerate the process of obtaining realistic images using the radiosity method. Two important concepts recently introduced are the general framework of projection methods and the hierarchical radiosity method.Wavelet theory, which explores the space of hierarchical basis functions, offers an elegant framework that unites these two concepts and allows us to more formally understand the hierarchical radiosity method.Wavelet expansions of the radiosity kernel have negligible entries in regions where high frequency/fine detail information is not needed. A sparse system remains if these entries are ignored. This is similar to applying a lossy compression scheme to the form factor matrix. The sparseness of the system allows for asymptotically faster radiosity algorithms by limiting the number of matrix terms that need to be computed. The application of these methods to 3D environments is described in4. Due to space limitations in that paper many of the subtleties of the construction could not be explored there. In this paper we discuss some of the mathematical details of wavelet projections and investigate the application of these methods to the radiosity kernel of a flatland environment, where many aspect are easier to visualize.en_US
dc.publisherBlackwell Science Ltd and the Eurographics Associationen_US
dc.titleWavelet Projections for Radiosityen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume13en_US
dc.description.number2en_US
dc.identifier.doi10.1111/1467-8659.1320141en_US
dc.identifier.pages141-151en_US


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