Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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An Image Processing Speed Enhancement in a Multi-Frame Super Resolution Algorithm by a CUDA Method

CUDA를 이용한 초해상도 기법의 영상처리 속도개선 방법

  • Received : 2011.04.27
  • Accepted : 2011.07.08
  • Published : 2011.08.05
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Abstract

Although multi-frame super resolution algorithm has many merits but it demands too much calculation time. Researches have shown that image processing time can be reduced using a CUDA(Compute unified device architecture) which is one of GPGPU(General purpose computing on graphics processing unit) models. In this paper, we show that the processing time of multi-frame super resolution algorithm can be reduced by employing the CUDA. It was applied not to the whole parts but to the largest time consuming parts of the program. The simulation result shows that using a CUDA can reduce an operation time dramatically. Therefore it can be possible that multi-frame super resolution algorithm is implemented in real time by using libraries of image processing algorithms which are made by a CUDA.

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References

  1. http://www.nvidia.com/object/cuda_education.html
  2. http://kr.nvidia.com/object/cuda_develop_kr.html
  3. http://www2.uic.edu/-agurmu2/CS525/final/
  4. Zhengyou Zhang, "A Flexible New Technique for Camera Calibration", Technical Report MSR-TR-98-71.
  5. Barbara Zitova and Jan Flusser, "Image Registration Methods : A Survey", Image and Vision Computing, Jun. 2003.
  6. S. C. Park, M. K. park and M. G. Kang, "Super- Resolution Image Reconstruction : A Technical Overview", IEEE Signal Processing Magazine, May. 2003.
  7. R. Y. Tsai and T. S. Huang, "Multipleframe Image Restoration and Registration", Advances in Computer Vision and Image Processing. Greenwich, CT : JAI Press Inc., pp. 317-339, 1984.
  8. Deshpande, S. D., "Max-Mean and MaxMedian Filters for Detection of Small-Targets", Conference on Signal And Data Processing of Small Targets, SPIE, Vol. 3809, pp. 74-83, 1999.

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