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.
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This work was supported by Research Funding of Huddersfield University: GPU-based High Performance Computing for Signal Processing (No. 1008/REU117).
Yang Su received the B. Sc. and M. Sc. degrees in communication and information systems from the Xi’an University of Science and Technology, PRC in 1994 and 1997, respectively. He then joined the School of Communication and Information Engineering within the same university as a member of academic staff in 1997 and became an associate professor in 2004. He is currently a Ph.D. candidate in computer science at the University of Huddersfield, UK.
His research interests include programmable switching, signal encoding/decoding, communication networks, and parallel processing.
Zhi-Jie Xu received the Ph.D. in virtual manufacturing at the University of Derby, UK in 2000. He is a senior lecturer and the head of the Computer Graphics and Image Processing Research Group within the School of Computing and Engineering at the University of Huddersfield, UK. He is a charted electronic engineer and a member of the IEEE, IET/IEE, British Computer Society (BCS), and UK Higher Education Academy (HEA).
His research interests include real-time graphics and vision systems, virtual reality (VR), manufacturing simulations, and Web-based e-technologies.
Xiang-Qian Jiang received the Ph.D. in measurement science at Huazhong University of Science and Technology, PRC in 1995. She was awarded a D. Sc. for precision engineering at University of Hudders-field, UK in 2007. She holds the chair of precision metrology at the Centre for Precision Technologies, University of Hudders-field, UK. She is a principle member of ISO TC/213 and the BSI TW/4, and a UK DIUS Measurement Advisory Committee member. She is a fellow of the Institute of Engineering Technology (IET), a fellow of the Royal Society of Arts, Manufacture and Commerce (RSA), and a member of the International Academy of Production Engineering (College International pour la Recherche en Productique, CIRP).
Her research interests include development of mathematical models and algorithms for surface metrology and development of new optical interferometry techniques for measurement of micro/nano-scale surface topography and form geometry.
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Su, Y., Xu, ZJ. & Jiang, XQ. Real-time virtual environment signal extraction and denoising using programmable graphics hardware. Int. J. Autom. Comput. 6, 326–334 (2009). https://doi.org/10.1007/s11633-009-0326-x
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DOI: https://doi.org/10.1007/s11633-009-0326-x