GPU-friendly rendering for illumination adjustable images

Ho, Tze-Yui; Lam, Ping-Man; Leung, Chi-Sing; Wong, Tien‐Tsin

doi:10.1016/j.image.2006.09.001

Cited by 3 publications

(2 citation statements)

References 37 publications

(35 reference statements)

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“…Recently, with the development of 3D GIS and GPU, massive terrain real-time rendering based on GPU comes up as a hot topic for research in computer graphics [7] . Sun Min developed a real-time LOD division method based on grid division.…”

Section: Related Workmentioning

confidence: 99%

Study on 3D visualization application for the Grand Canal heritage site research

Fan

Tan

et al. 2009

SPIE Proceedings

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This study focuses on two problems in 3D visualization application for heritage site research. Firstly, methods for large scale terrain modeling and rendering were presented. Complex virtual environments were constructed with sequences of remote sensing images and DEM data. The algorithm of precise 3D scenes modeling was optimized. At the same time, the spatial index of quadtree and the images cache management strategies were introduced for improving the performance of interactive 3D visualization system. A novel method creating a mapping between 3D models and the image textures were put forward, so that the models and the textures can be managed respectively. As a result, the capacity of massive 3D terrain surface models management was enhanced as well as the real-time rendering was accelerated. Secondly, methods for 3D culture relics modeling were presented. The culture relics and ancient buildings of the Canal were simulated, which will contribute to its reconstruction and protection. Some ancient water facilities such as ship-lock and docks models and animated navigation scenes were created based on the construction principle and architecture of the Canal transport hub.

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Section: Related Workmentioning

confidence: 99%

Study on 3D visualization application for the Grand Canal heritage site research

Fan

Tan

et al. 2009

SPIE Proceedings

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“…The writers of [6] have presented and analyzed different implementations of mass-spring systems for interactive simulation of deformable surfaces on GPUs. Ho [7] presents practical and real-time rendering methods for illumination adjustable image (IAI) based on spherical Gaussian kernel functions. Heimlich et al [1] evaluated the impact of using GPU in two computational expensive problems in nuclear area: a neutron transport simulation by Monte Carlo method and Poisson heat equation resolution for a square thin plate.…”

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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