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Images rendered using global illumination algorithms are considered amongst the most realistic in 3D computer graphics. However, this high fidelity comes at a significant computational expense. A major part of this cost arises from the sampling required to eliminate aliasing errors. These errors occur due to the discrete sampling of continuous geometry space inherent to these techniques. In this paper we present a fast analytic method for predicting in advance where antialiasing needs to be computed. This prediction is based on a rapid visualisation of the scene using a GPU, which is used to drive a selective renderer. We are able to significantly reduce the overall number of anitialiasing rays traced, producing an image that is perceptually indistinguishable from the high quality image at a much reduced computational cost.

The media industry is demanding increasing fidelity for their rendered images. Despite the advent of modern GPUs, the computational requirements of physically based global illumination algorithms are such that it is still not possible to render high-fidelity images in real time. The time constraints of commercial rendering are such that the user would like to have an idea as to just how long it will take to render an animated sequence, prior the actual rendering. This information is necessary to determine whether the desired quality is achievable in the time available or indeed if it is possible to afford to carry out the work on a render farm for example. This paper presents a comparison of different pixel profiling strategies which may be used to predict the overall rendering cost of a high fidelity global illumination solution. A fast rasterised scene preview is proposed which provides a more accurate positioning and weighting of samples, to achieve accurate cost prediction.

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