DOI QR코드

DOI QR Code

The Enhancement of the Boundary-Based Depth Image

경계 기반의 깊이 영상 개선

  • Received : 2011.12.16
  • Accepted : 2012.03.09
  • Published : 2012.04.30

Abstract

Recently, 3D technology based on depth image is widely used in various fields including 3D space recognition, image acquisition, interaction, and games. Depth camera is used in order to produce depth image, various types of effort are made to improve quality of the depth image. In this paper, we suggests using area-based Canny edge detector to improve depth image in applying 3D technology based on depth camera. The suggested method provides improved depth image with pre-processing and post-processing by fixing image quality deterioration, which may take place in acquiring depth image in a limited environment. For objective image quality evaluation, we have confirmed that the image is improved by 0.42dB at maximum, by applying and comparing improved depth image to virtual view reference software. In addition, with DSCQS(Double Stimulus Continuous Quality Scale) evaluation method, we are reassured of the effectiveness of improved depth image through objective evaluation of subjective quality.

최근 깊이영상을 기반으로 한 3D 기술이 3D 공간감지, 3D 영상획득, 3D 인터랙션, 3D 게임 등 다양한 분야에서 응용되고 있다. 깊이영상을 생성하기 위해서는 깊이 카메라를 이용하게 되는데, 이렇게 생성된 깊이영상의 화질을 개선하기 위한 다양한 시도들이 이루어지고 있다. 본 눈문에서는 이러한 깊이 카메라 기반의 3D 응용에 있어서 깊이 영상을 개선하기 위해 영역기반의 에지 검출기를 사용하는 방법을 제안한다. 제안된 방법은 제한된 환경에서의 깊이영상을 획득하는 과정에서 발생 할 수 있는 화질열화를 후처리 또는 전처리를 통해 개선함으로써 보다 향상된 깊이 영상을 제공한다. 다양한 실험결과를 통해서 개선된 깊이영상을 객관적 화질 평가를 위해 가상시점 참조 소프트웨어에 적용하여 비교함으로써 최대 0.42dB의 화질 향상을 확인하였다. 또한 영상의 실제 시청 환경과 가장 유사한 방법인 DSCQS(Double Stimulus Continuous Quality Scale)방법을 통해서 주관적 화질의 객관적 평가를 수행함으로써 개선된 깊이영상의 효용성을 다시 확인하였다.

Keywords

References

  1. K.H.Shon, "3D Video Coding Technology", Optical Society of Korea, vol. 5, pp.32-37, Jun 2001.
  2. K.S.Park, "3D TV Broadcasting Technology", Communication Books, 2004.
  3. ISO/IEC JTC1/SC29/WG11 N9783, "Description of Exploration Experiments in 3D Video Coding" Maui, Hawaii, Feb 2009.
  4. W.R. Mark, L. McMillan, and G. Bishop, "Post-rendering 3D warping," Proc. of Symposium on Interactive 3D Graphics, pp. 7-16, Apr 1997.
  5. C. Zitnick, S. Kang, M. Uyttendaele, S. Winder, and R. Szeliski, "High-quality video view interpolation using a layered representation" SIGGRAPH, pp. 600-608, Aug 2004.
  6. L. Zhang and W. J. Tam, "Stereoscopic image generation based on depth images for 3D TV," IEEE Trans. on Broadcasting, vol. 51, pp.191-199, May 2005. https://doi.org/10.1109/TBC.2005.846190
  7. Erhan Ekmekcioglu, Vladan Velisavljevi´, and Stewart T. Worrall, "Efficient edge, motion and depth-range adaptive processing for enhancement of multi-view depth map sequences" 16th IEEE International Conference on Image Processing (ICIP), pp.3537-3540, Feb 2009.
  8. Erhan Ekmekcioglu, Vladan Velisavljevi´, and Stewart T. Worrall, "Edge and motion-adaptive median filtering for multi-view depth map enhancement" Picture Coding Symposium (PCS), pp. 1-4, Jul 2009.
  9. John Canny, "A Computational Approach to Edge Detection" IEEE Trans.k on pattern analysis and machine intelligence, Vol. PAMI-8, No. 6, Nov 1986.
  10. A. Ignatenko and A. Konushin, "A framework for depth image based modeling and rendering," Proc. Graphicon, pp.169-172, Sep 2003.
  11. ITU-R Recommendation BT.500-11, "Methodology for subjective assessment of the quality of television picture".
  12. online available:http://wg11.sc29.org/svn/repos/MPEG-4/test/trunk/3D/view_synthesis/VSRS
  13. online available:http://www.tanimoto.nuee.nagoya-u.ac.jp/mpeg/mpeg_ftv.html.
  14. ISO/IEC JTC1/SC29/WG11 N7539, "Requirements on Multi-view Video Coding", Nice, France, Vol. 5 Oct 2005.