Fast algorithms for pre-filtered anti-aliasing previously operated solely on straight line objects; this work extends the class of objects to include circles and ellipses. The new algorithms do not require floating po...
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Fast algorithms for pre-filtered anti-aliasing previously operated solely on straight line objects; this work extends the class of objects to include circles and ellipses. The new algorithms do not require floating point, square root, or division operations in the inner loops. When rendering against a constant background, a single inner loop multiapplication operation may also be eliminated. We describe in detail how the technique is applied to rendering an octant of a filled circle using a square area integration filter. We briefly describe the extensions necessary for different types of anti-aliased circles and ellipses. We show how pre-computed filters stored in a lookup table may be implemented.
A natural language based color naming system for color raster graphics, the Artist's Color Naming System (ACNS), is introduced. ACNS is an English-based nomenclature which is a high-level alternative to the numeri...
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This paper focuses on the problem of management of CAD data by investigating the use of the software engineering principles of data abstraction and object-oriented programming as means for managing the volume and comp...
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In order to make computer programs more readable, understandable, appealing, memorable, and maintainable, the presentation of program source text needs to be enhanced over its conventional treatment. Towards this end,...
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Standardization of a high performance blackplane bus, so that it can accommodate boards developed by different vendors, implies the need for a standardized cache consistency protocol. In this paper we define a class o...
ISBN:
(纸本)9780818607196
Standardization of a high performance blackplane bus, so that it can accommodate boards developed by different vendors, implies the need for a standardized cache consistency protocol. In this paper we define a class of compatible consistency protocols supported by the current IEEE Futurebus design. We refer to this class as the MOESI class of protocols; the term “MOESI” is derived from the names of the states. This class of protocols has the property that any system component can select (dynamically) any action permitted by any protocol in the class, and be assured that consistency is maintained throughout the system. Included in this class are actions suitable for copyback caches, write through caches and non-caching processors. We show that the Berkeley protocol and the Dragon protocol fall within this class, and can be extended to be compatible with other members of the class. The Illinois, Firefly and Write-Once protocols can be adapted to be compatible with this class; the facilities of he Futurebus currently do not support those protocols without adaptation. We discuss very briefly performance choices among protocols, and also other issues relating to a standard bus consistency protocol.
This paper reports on an interactive system for manipulating a tensor-product B-spline approximation to field data for applications in which contours are of interest. The features of the system are: an interpolation t...
ISBN:
(纸本)9780897912136
This paper reports on an interactive system for manipulating a tensor-product B-spline approximation to field data for applications in which contours are of interest. The features of the system are: an interpolation technique for approximating fields defined from scattered or gridded data by tensor-product B-splines, an interactive display providing control-vertex manipulation of the resulting B-spline approximation, and a contouring algorithm that is designed specifically for B-spline surfaces.
Five primary approaches to texture synthesis for computergraphics are surveyed: a syntactic approach, a statistical approach, a growth model approach, a computer drafting approach, and a stochastic modeling approach....
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Five primary approaches to texture synthesis for computergraphics are surveyed: a syntactic approach, a statistical approach, a growth model approach, a computer drafting approach, and a stochastic modeling approach. Most of these methods, derived from texture analysis techniques or from mathematical models of texture, have a relatively low-level, cumbersome way to define, manipulate, or input textures. As an alternative, a high-level language approach is proposed. It provides easy-to-use coding mechanisms to define, synthesize, and manipulate textures. The high-level approach is introduced by means of the Texture Synthesis Language (TSL).
A number of sound synthesis methods rely on computing samples of a waveform from a mathematical description of the continuous signal. Such methods would include, for example, waveshaping, frequency modulation (FM), an...
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A number of sound synthesis methods rely on computing samples of a waveform from a mathematical description of the continuous signal. Such methods would include, for example, waveshaping, frequency modulation (FM), and wavetable synthesis. All of these techniques presently suffer from aliasing defects if the continuous waveform being sampled has significant energy above half the Nyqnist rate. However, this defect is not inherent in the description of the signal, but only in the nature of the regular sampling process. In this paper, stochastic sampling techniques, in particular Poisson and jittered sampling, are developed 'and analyzed in the time and frequency domains. Such techniques have already been used to generate alias-free power spectrum estimates [14] and to antialias computergraphics images [10, 11]. In sound synthesis, it is shown that these techniques allow the construction of alias-free approximations to signals at any sampling rate, regardless of the bandwidth or frequency content of the continuous signal. Stochastic sampling scatters high frequency components into broadband noise rather than folding them down into the audio range as in regular sampling. Broadband noise is more benign than narrowband aliases with similar energy. The probabilistic structure of the random sampling process controls the general spectral shape of the added noise. The spectrum of the noise for the sampling techniques mentioned above is described explicitly. Also, an explicit relationship is developed between the total signal to noise ratio and various parameters of the process, such as the the average sampling rate and the bandwidth of the continuous signal being sampled. Since the nature of the noise is known, noise reduction techniques can be used to increase the efficacy of a given average sampling rate. The stochastic sampling technique can be applied adaptively so that a greater number of samples are taken where the function varies most. An error estimate is used to det
Stochastic sampling techniques, in particular Poisson and fittered sampling, are developed and analyzed. These approaches allow the construction of alias-free approximations to continuous functions using discrete calc...
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ISBN:
(纸本)9780897911665
Stochastic sampling techniques, in particular Poisson and fittered sampling, are developed and analyzed. These approaches allow the construction of alias-free approximations to continuous functions using discrete calculations. Stochastic sampling scatters high frequency information into broadband noise rather than generating the false patterne produced by regular sampling. The type of randomness used in the sampling process controls the spectral character of the noise. The average sampling rate and the function being sampled determine the amount of noise that is produced. Stochastic sampling is applied adaptively so that a greater number of samples are taken where the function varies most. An estimate is used to determine how many samples to take over a given region. Noise reducing filters are used to increase the efficacy of a given sampling rate. The filter width is adaptively controlled to further improve performance. Stochastic sampling can be applied spatiotemporally as well as to other aspects of scene simulation. Ray tracing is one example of an image synthesis approach that can be antialiased by stochastic sampling.
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