방송공학회논문지 (Journal of Broadcast Engineering)

  • 제21권6호
  • /
  • Pages.920-928
  • /
  • 2016
  • /
  • 1226-7953(pISSN)
  • /
  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
권호 표지
DOI QR코드

DOI QR Code

가중 최소자승 필터링과 색 표현 모델을 결합한 넓은 동적 영역 이미지 표현

High Dynamic Range Image Display Combining Weighted Least Squares Filtering with Color Appearance Model

  • 박미선 (한양대학교 전자컴퓨터통신공학과) ;
  • 이경준 (한양대학교 전자컴퓨터통신공학과) ;
  • 위승우 (한양대학교 전자컴퓨터통신공학과) ;
  • 정제창 (한양대학교 전자컴퓨터통신공학과)
  • Piao, Mei-Xian (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Lee, Kyung-Jun (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Wee, Seung-Woo (Department of Electronics and Computer Engineering, Hanyang University) ;
  • Jeong, Jechang (Department of Electronics and Computer Engineering, Hanyang University)
  • 투고 : 2016.09.20
  • 심사 : 2016.11.21
  • 발행 : 2016.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

최근 넓은 동적 영역 이미지 기술은 컴퓨터 그래픽 분야에서 화제다. 본 논문에서는 가중 최소자승(가중회귀분석) 최적화 체계에 기반하여 넓은 동적 영역 이미지를 처리하는 톤매핑 알고리듬을 제안한다. 제안하는 방법은 시각적 후광 현상을 피하는 동시에 기존의 디스플레이에서 더 지각적인 넓은 동적 영역 이미지들을 보여주기 위해 가중 최소자승 필터링과 iCAM06모델을 결합한다. 제안된 알고리듬은 먼저 넓은 동적 영역 이미지를 base layer와 detail layer로 나눈다. Base layer는 큰 규모의 변화량을 가지고 있으며 가중 최소자승 필터링을 사용하여 얻어지고 iCAM06 모델을 포함한다. 다음으로, 인간의 시각 체계에 따라 base layer는 적응적으로 압축된다. 압축 시에는 base layer만 대비를 줄이고 detail layer을 보존한다. 본 논문에서는 객관적 화질 평가와 주관적 화질 평가를 통하여 제안하는 알고리듬을 적용한 이미지가 기존의 알고리듬을 적용한 이미지들에 비해 원본 넓은 동적 영역 이미지에 더 유사하다는 것을 보여준다.

Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted least squares filtering with iCAM06 model. To show more perceptual high dynamic range images in conventional display, we decompose high dynamic range image into base layers and detail layers. The base layers are obtained by using weighted least squares filter. Then, we adopt chromatic adaption function and non-linear compression function to deal with base layers. Only the base layers reduce contrast, and preserving detail. The image quality assessment shows that our tone mapped image is more similar to original high dynamic range image. Moreover, the subjective result shows our algorithm produces more reliable and pleasing image.

키워드

참고문헌

  1. D. Park, J. Kim, S. Lim, J. Kim, and H. Kim, "LCU-Level Rate Control for HEVC Considering Hierarchical Coding Structure," Journal of Broadcast Engineering, vol. 16, no. 5, pp. 762-772, 2011. https://doi.org/10.5909/JEB.2011.16.5.762
  2. Y. Kim, J. Choi, and H. Choi, "Performance Analysis of Scalable HEVC Coding Tools," Journal of Broadcast Engineering, vol. 20, no. 4, pp. 497-508, 2015. https://doi.org/10.5909/JBE.2015.20.4.497
  3. J. Lim, Y. Ahn, W. Lim, S. Park, D. Sim, and J. Kang, "Layered Coding Method for Scalable Coding of HDR and SDR videos," Journal of Broadcast Engineering, vol. 20, no. 5, pp. 756-769, 2015. https://doi.org/10.5909/JBE.2015.20.5.756
  4. E. Francois, C. Fogg, Y. He, X. Li, A. Luthra, and A. Segall, "High Dynamic Range and Wide Color Gamut Video Coding in HEVC: Status and Potential Future Enhancements," IEEE Trans. Circuits Syst. Video Technol., vol. 26, no. 1, pp. 63-75, Jan. 2016. https://doi.org/10.1109/TCSVT.2015.2461911
  5. Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, "Edge-preserving decompositions for multi-scale tone and detail manipulation," ACM Trans. Graph., vol. 27, Iss. 3, Aug. 2008.
  6. J. Kuang, G. Johnson, and M. Fairchild, "iCAM06: A refined image appearance model for HDR image rendering," Journal of Visual Communication and Image Representation, vol. 18, Iss. 5, pp. 406-414, 2007. https://doi.org/10.1016/j.jvcir.2007.06.003
  7. M. Fairchild, G. Johnson, "Meet iCAM: A next-generation color appearance model," IS& T/SID 10th Color Imaging Conference, pp. 33-38, 2002.
  8. F. Durand, J. Dorsey, "Fast bilateral filtering for the display of high-dynamic-range images," ACM Trans. Graph., vol. 21, no.3, pp. 257-266, 2002.
  9. P. Perona and J. Malik, "Scale-space and edge detection using anisotropic diffusion," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 7, pp. 629-639, 1990. https://doi.org/10.1109/34.56205
  10. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," In Proc. IEEE Int. Conf. on Computer Vision, pp. 836-846, 1998.
  11. D. Lischinski, Z. Farbman, M. Uyttendaele, and R. Szeliski, "Interactive local adjustment of tonal values," ACM Trans. Graph., vol. 25, no. 3, pp. 646-653, 2006. https://doi.org/10.1145/1141911.1141936
  12. H. Yeganeh and Z. Wang, "Objective Quality Assessment of Tone-Mapped Images," IEEE Trans. Image Process., vol. 22, no. 2, pp. 657-667, Feb. 2013. https://doi.org/10.1109/TIP.2012.2221725
  13. K. Ma, H. Yeganeh, K. Zeng, and Z. Wang, "High Dynamic Range Image Compression by Optimizing Tone Mapped Image Quality Index," IEEE Trans. Image Process., vol. 24, no. 10, pp. 3086-3097, Oct. 2015. https://doi.org/10.1109/TIP.2015.2436340
  14. F. Drago, K. Myszkowski, T. Annen, and N. Chiba, "Adaptive Logarithmic Mapping For Displaying High Contrast Scenes," Computer Graphics forum, vol. 22, Iss. 3, pp. 419-426, Sep. 2003. https://doi.org/10.1111/1467-8659.00689
  15. R. Mantiuk, A. Tomaszewska, and W. Heidrich, "Color correction for tone mapping," Computer Graphics forum, vol. 28, Iss. 2, pp. 193-202, April 2009. https://doi.org/10.1111/j.1467-8659.2009.01358.x