Wavelets in computer graphics

Schröder, Peter

doi:10.1109/5.488703

Cited by 49 publications

(11 citation statements)

References 64 publications

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“…Moreover, we have also witnessed the increasing presence of the DWT in computer graphics [17], which emphasizes the relevance of our study. Driven by its popularity and by the realtime needs of many image processing tasks, significant research work has been done on its efficient implementation on all sorts of computer systems.…”

Section: Related Worksupporting

confidence: 58%

Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting

Tenllado

Setoaín

Prieto

et al. 2008

IEEE Trans. Parallel Distrib. Syst.

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Abstract-The widespread usage of the discrete wavelet transform (DWT) has motivated the development of fast DWT algorithms and their tuning on all sorts of computer systems. Several studies have compared the performance of the most popular schemes, known as Filter Bank Scheme (FBS) and Lifting Scheme (LS), and have always concluded that LS is the most efficient option. However, there is no such study on streaming processors such as modern Graphics Processing Units (GPUs). Current trends have transformed these devices into powerful stream processors with enough flexibility to perform intensive and complex floating-point calculations. The opportunities opened up by these platforms, as well as the growing popularity of the DWT within the computer graphics field, make a new performance comparison of great practical interest. Our study indicates that FBS outperforms LS in current-generation GPUs. In our experiments, the actual FBS gains range between 10 percent and 140 percent, depending on the problem size and the type and length of the wavelet filter. Moreover, design trends suggest higher gains in future-generation GPUs.

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Section: Related Worksupporting

confidence: 58%

Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting

Tenllado

Setoaín

Prieto

et al. 2008

IEEE Trans. Parallel Distrib. Syst.

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“…Data structures adapted to wavelet implementation have been extensiveley studied in the computer graphics community [48]. Wavelets are used in different subfields of this community, such as: image compression, automatic level-of-detail control for editing and rendering curves and surfaces, global illumination, volume rendering, rendering of complex scenes in real time.…”

Section: Related Work and Discussionmentioning

confidence: 99%

Sparse data structure design for wavelet-based methods

Latu

2011

ESAIM: Proc.

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Abstract. This course gives an introduction to the design of efficient datatypes for adaptive waveletbased applications. It presents some code fragments and benchmark technics useful to learn about the design of sparse data structures and adaptive algorithms. Material and practical examples are given, and they provide good introduction for anyone involved in the development of adaptive applications. An answer will be given to the question: how to implement and efficiently use the discrete wavelet transform in computer applications? A focus will be made on time-evolution problems, and use of wavelet-based scheme for adaptively solving partial differential equations (PDE). One crucial issue is that the benefits of the adaptive method in term of algorithmic cost reduction can not be wasted by overheads associated to sparse data management.

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“…Wavelets are used to create sets of models of 3 dimensional objects for on-screen rendering. As an object moves toward the foreground of an image, more complex models are used to display finer detail (Schröder 1996).…”

Section: Kantnermentioning

confidence: 99%

Hierarchical modeling and multiresolution simulation

Kantner¹

1999

Proceedings of the 31st Conference on Winter Simulation Simulation---a Bridge to the Future - WSC '99

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As systems become more complex, the need to explicitly account for uncertainty during modeling and simulation grows. The interactions between assumptions made in modeling different subsystems may greatly affect system behavior. Unless these assumptions are quantified and included in the simulation, results can be misleading or even completely wrong.Piecewise linear (PL) modeling is proposed as a method for quantifying the uncertainty in a model. With PL models, sets of models with varying amounts of uncertainty are easily developed. Robust simulation is then used to account for uncertainty during analysis. Also, robust simulation allows dynamic selection of models. Through the use of PL modeling and robust simulation, unexpected model interaction can be predicted.These techniques are demonstrated on 3 simple illustrative examples. A model library is developed for a saturation. This saturation is then used in a feedback system, and the simulation results of various models are examined. A final example demonstrates the benefits of changing model accuracy during simulation.

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Wavelets in computer graphics

Cited by 49 publications

References 64 publications

Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting

Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting

Sparse data structure design for wavelet-based methods

Hierarchical modeling and multiresolution simulation

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