1691

Real-time virtual environment signal extraction and denoising using programmable graphics hardware

Yang Su, Zhi-Jie Xu, Xiang-Qian Jiang
School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
International Journal of Automation and Computing, Vol. 6, No. 4. (1 November 2009), pp. 326-334

@article{su2009real,

   title={Real-time virtual environment signal extraction and denoising using programmable graphics hardware},

   author={Su, Y. and Xu, Z.J. and Jiang, X.Q.},

   journal={International Journal of Automation and Computing},

   volume={6},

   number={4},

   pages={326–334},

   issn={1476-8186},

   year={2009},

   publisher={Springer}

}

Download Download (PDF)   View View   Source Source   

613

views

Abstract The sense of being within a three-dimensional (3D) space and interacting with virtual 3D objects in a computer-generated virtual environment (VE) often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and wavelet-based image denoising algorithms that run on the graphics processing unit (GPU). While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence (AI) and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: