High Performance GPU-Based Fourier Volume Rendering

Abdellah, Marwan; Eldeib, Ayman M.; Sharawi, Amr A.

doi:10.1155/2015/590727

Cited by 7 publications

(3 citation statements)

References 21 publications

(23 reference statements)

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“…From this perspective, the proposed method generally demonstrates an acceptable time performance. In addition, some image processing methods in GPU would be used to accelerate the rendering procedure [37,38]. As future extensions, optimizations like parallelization through GPUs and multicore CPUs to compute multiscale field coupling can still be made; thus a significant speed-up can be expected.…”

Section: Computational Complexitymentioning

confidence: 99%

Field Coupling-Based Image Filter for Sand Painting Stylization

Xia

2018

Mathematical Problems in Engineering

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Sand painting is a very new and popular performance art technique, and it has important meaning for the artistic creation. Computer-aided sand painting is now in the ascendant, whose fully automated mechanism is still an attractive challenge. Image data field, inspired from short-range nuclear force in physics, is introduced into sand painting stylization. With preserving edges and features, a fully automatic image filter pipeline based on image field coupling is proposed, which consists of three main steps, including image data field generating, multiscale field coupling, and additional details optimizing. The visual comparisons indicate that the proposed pipeline and image filter are feasible and effective, and sand painting-like artistic images can be produced by using multiscale field coupling. The qualities of various rendering images are also investigated from the perspective of feature similarity measures. The quantitative and qualitative results suggest that the field coupling-based filter is appropriate for sand painting stylization, and the time cost is satisfied for practice applications. Generally, the proposed method provides a reference for automatic creation of computer-aided sand painting art.

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Section: Computational Complexitymentioning

confidence: 99%

Field Coupling-Based Image Filter for Sand Painting Stylization

Xia

2018

Mathematical Problems in Engineering

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“…It can be accelerated by GPU, but its imaging quality is not good enough to clinical applications. 5 Object-order (forward mapping) VR calculates contribution of each data point to image pixels from close to distant or exactly opposite to create a screen image. 6 Not only does its complexity reach to O N 3 , but also its imaging quality is poor.…”

Section: Related Workmentioning

confidence: 99%

Fast Graphic Processing Unit-Based High-Quality Three-Dimensional Volume Rendering

Feng¹,

Hu²,

Yang³

et al. 2016

j med imaging hlth inform

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Volume rendering (VR) is powerful in visualizing meaningful information existing in medical images. However, due to its high computational complexity, it is hard for VR to achieve high-quality real-time interaction. In this paper, a GPU-based VR method is first proposed in which volume texture mapping is used. To reduce requirements of the proposed method on storage of video memory, the proposed method is further improved by using slice texture with a real-time dynamic switch mechanism. Moreover, to eliminate annular distortion, a pre-integration classification method, which is implemented on GPUs, is presented. Experimental results demonstrate that (1) frame rates of the texture mapping methods are almost the same for small-scale volume data, (2) for large-scale volume data, volume texture based method failed, but frame rate of the further improved (slice texture mapping) method is still up to 20 FPS, and (3) the pre-integration method presented in this paper can improve rendering quality effectively with FPS preserved.

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“…CUDA can, also, help scientists and engineers to access GPU as they accessed CPU before, by simple programming codes. Nowadays, GPUs are able to execute various science and engineering algorithms, up to more than 100 times faster than similar-cost CPUs [5] (when the CPU code is single-threaded) and up. Nowadays, almost every researcher has a programmable GPU inside his computer and may not be advised about this unused power, which can be accessed by simple and similar programming codes to what they did before.…”

Section: Introduction 1graphics Processing Unitmentioning

confidence: 99%

GPU-Acceleration of Parallel Unconditionally Stable Group Explicit Finite Difference Method

Parand¹,

Zafarvahedian²,

Hossayni³

2013

Preprint

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Graphics Processing Units (GPUs) are high performance co-processors originally intended to improve the use and quality of computer graphics applications. Once, researchers and practitioners noticed the potential of using GPU for general purposes, GPUs applications have been extended from graphics applications to other fields. The main objective of this paper is to evaluate the impact of using GPU in solution of the transient diffusion type equation by parallel and stable group explicit finite difference method and encourage the researchers in this field to immigrate from implementing their algorithms in CPU to the GPU emerging world. For comparing them, we implemented the method in both GPU and CPU (multi-core) programming context. Moreover, we proposed an optimal synchronization arrangement for the implementation pseudo-code. Also, the interrelation of GPU parallel programming and initializing the algorithm variables were discussed, taking advantage of numerical experiences. The GPU-approach results are faster than those obtained from a much expensive parallel 8-thread CPU-based programming. The GPU used in this paper, is an ordinary old laptop GPU (GT 335M, launched at 2010) and is accessible for everyone and the newer generations of GPU (as discussed in paper) have even more performance priority over the similar-price GPUs. Then, the results are expected to encourage the entire research society to take advantage of GPUs and improve the time efficiency of their studies.

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High Performance GPU-Based Fourier Volume Rendering

Cited by 7 publications

References 21 publications

Field Coupling-Based Image Filter for Sand Painting Stylization

Field Coupling-Based Image Filter for Sand Painting Stylization

Fast Graphic Processing Unit-Based High-Quality Three-Dimensional Volume Rendering

GPU-Acceleration of Parallel Unconditionally Stable Group Explicit Finite Difference Method

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