Abstract: A computer graphics system generates a pixel value for a pixel in an image, the pixel value being representative of a point in a scene as recorded on an image plane of a simulated camera, the computer graphics system comprising a sample point generator and a function evaluator. The sample point generator is configured to generate a set of sample points, at least one sample point being generated using at least one dependent sample, the at least one dependent sample comprising at least one element of a low-discrepancy sequence offset by at least one element of another low-discrepancy sequence. The function evaluator is configured to generate at least one value representing an evaluation of a selected function at one of the sample points generated by the sample point generator, the value generated by the function evaluator corresponding to the pixel value.

Abstract: A computer graphics system generates pixel values for pixels in an image of objects in a scene, using strictly-deterministic low-discrepancy sequences, as sample points for evaluating integrals which are used to simulate a number of computer graphic techniques, including soft shadows generated for scenes illuminated by a light source having a finite extent, such as a disk, simulation of depth of field; motion blur; and jittering. The computer graphics system uses the low-discrepancy sequence to generate sample points. The low discrepancy sequences ensure that the sample points are evenly distributed over a respective region or time interval, thereby reducing error in the image which can result from clumping of such sample points which can occur in the Monte Carlo technique. The invention facilitates the generation of images of improved quality when using the same number of sample points at the same computational cost as in the Monte Carlo technique.

Abstract: A computer graphics system generates a pixel value for a pixel in an image, the pixel being representative of a point in a scene. The computer graphics system generates the pixel value by an evaluation of an integral of a selected function. The computer graphics system comprises a sample point generator and a function evaluator. The a sample point generator is configured to generate respective sets of sample points each associated with one of a series of rays in a ray trace configured to have a plurality of trace levels. The ray at at least one level can be split into a plurality of rays, with each ray being associated with a ray instance identifier. The sample point generator is configured to generate the sample points as predetermined strictly-deterministic low-discrepancy sequence to which a selected rotation operator is applied recursively for the respective levels.

Abstract: A computer graphics system generate a pixel value for a pixel in an image to simulate global illumination represented by an evaluation of an unknown function ƒ of the form f ? ( x ) = g ? ( x ) + ? 0 1 ? K ? ( x , y ) ? f ? ( y ) ? ? ? ? y , g(x) and K(x,y) known functions, with K(x,y) a “kernel” including a function associated with at least two colors.

Abstract: A computer graphics system generates pixel values for pixels in an image of objects in a scene, using strictly-deterministic low-discrepancy sequences, illustratively Halton sequences, as sample points for evaluating integrals which are used to simulate a number of computer graphic techniques, including:

Abstract: A computer graphics system and a method for generating pixel values in an image of objects using strictly-deterministic low-discrepancy sequences as sample points for evaluating integrals which are used to simulate a number of computer graphic techniques including soft shadows, simulation of depth of field, motion blur, jittering, and global illumination. Unlike the random numbers used in connection with the Monte Carlo technique, the low discrepancy sequences ensure that the sample points are evenly distributed over a respective region or time interval, thereby reducing clumping of such sample points. The invention facilitates the generation of images of improved quality when using the same number of sample points at the same computational cost as in the Monte Carlo technique.

Abstract: A computer graphics system is described in which a new type of entity, referred to as a “phenomenon,” can be created, instantiated and used in rendering an image of a scene. A phenomenon is an encapsulated shader DAG comprising one or more nodes each comprising a shader, or an encapsulated set of such DAGs which are interconnected so as to cooperate, which are instantiated and attached to entities in the scene which are created during the scene definition process to define diverse types of features of a scene, including features which are useful in rendering. Prior to being attached to a scene, a phenomenon is instantiated by providing values, or functions which are used to define the values, for each of the phenomenon's parameters. During scene image generation, a scene image generator operates in a series of phases. During a pre-processing phase, the scene image generator can perform pre-processing operations, such as shadow and photon mapping, multiple inheritance resolution, and the like.