Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

WENO methodology for UHD TV Image Quality Improvement

WENO 방법을 이용한 UHD TV 화질 개선

  • Yi, Dokkyun (Division of Mechanical Engineering, Daegu University) ;
  • Park, Jieun (Seong-san Liberal Arts College, Daegu University)
  • 이덕균 (대구대학교 공과대학 기계공학부) ;
  • 박지은 (대구대학교 인문교양대학)
  • Received : 2018.02.14
  • Accepted : 2018.04.20
  • Published : 2018.04.28
Download PDF
⟨ Previous Next ⟩

Abstract

It has passed the era of Full High Definition Television (FHD) and ended the era of Ultra High Definition Television (UHD). We will talk about the problems caused by the difference in the number of pixels in the TVs and introduce a method to improve them. This method is a method of performing an interpolation method suitable for a given image with Weighted Essential Non-Oscillation (WENO). Thus, it is possible to reduce the distortion of the image and to ensure a better image quality. Therefore, if we use the WENO methodology, when we watch old video material on UHD TV, we can enjoy high definition of UHD TV without changing the number of pixels.

FHD(Full High Definition Television)의 시대를 지나 UHD(Ultra High Definition Television) 시대를 맞이하였다. 두 TV에서 화소(Pixel)수의 차이에 따라 발생하는 문제에 대하여 이야기하고 이를 개선할 수 있는 방법을 도입하고자 한다. 이 방법은 WENO(Weighted Essential Non-Oscillation)으로 주어진 영상(Image)에 적합한 보간법을 시행하는 방법이다. 이를 통하여 영상의 왜곡현상을 줄이고 보다 나은 화질을 보장할 수 있다. 따라서 예전에 만들어진 영상물을 UHD TV로 시청하려고 할 때 WENO 방법론을 활용하면 화소수에 따른 화질의 저하 없이 UHD TV의 고화질을 누릴 수 있다.

Keywords

References

  1. M. Sugawara, M. Kanazawa, K. Mitani & F. Okano. (2003. Oct). Ultrahigh-Definition Video System with 4000 Scanning Lines. SMPTE Motion Imaging Journal, 112, 339-346. https://doi.org/10.5594/J16304
  2. T. Blu, P. Thevenaz & M. Unser. (2004). Linear interpolation revitalized. IEEE Trans. on Image Processing, 13(5), 710-719. https://doi.org/10.1109/TIP.2004.826093
  3. R. G. Keys. (1981). Cubic convolution interpolation for digital image processing. IEEE Trans. on Acoust., Speech, Signal Process, ASSP-29(6), 1153-1160.
  4. W. C. Siu & K. W. Hung. (2012). Review of Image Interpolation and Super-resolution. IEEE conference. ieeexplore.ieee.org/document/6411957.
  5. D. H. Han. (2016). Design and Characteristics of 6-60 Lens for CCTV. Journal of Convergence Society for SMB, 6(3), 85-91.
  6. N. Crouseilles, T. Respanud & E. Sonnendrucker. (2009). A Forward semi-Lagrangian method for the numerical solution of the Vlasov equation. Computer Physics Communications, 180, 1730-1745. https://doi.org/10.1016/j.cpc.2009.04.024
  7. E. Sonnendrucker, J. Roche, P. Bertrand & A. Ghizzo. (1999). The semi-lagrangian method for the numerical resolution of the Vlasov equation. Journal of Computer Physics, 149, 201-220. https://doi.org/10.1006/jcph.1998.6148
  8. A. Staniforth & J. Cote. (1991). Semi-Lagrangian integration schemes for atmospheric models. A review Mon. Weather Rev. 119, 2206-2223. https://doi.org/10.1175/1520-0493(1991)119<2206:SLISFA>2.0.CO;2
  9. M. Zerroukat, N. Wood & A. Staniforth. (2005). A monotonic and positive-definite filter for a Semi-Lagrangian Inherently Conserving and Efficient (SLICE) scheme. Q. J. R. Meteorol. Soc. 131, 2923-2936. https://doi.org/10.1256/qj.04.97
  10. G.. S. Jiang & C.-W. Shu. (1996). Efficient implementation of weighted ENO schemes. Journal of Computational Physics, 126, 202-228. https://doi.org/10.1006/jcph.1996.0130
  11. X. D. Liu, S. Osher & T. Chan. (1994). Weighted essentially non-oscillatory schemes, Journal of Computational Physics, 115, 200-212. https://doi.org/10.1006/jcph.1994.1187
  12. S. J. Kim & D. E. Cho. (2018). Study on Learning Model for Effective Coding Education. Journal of the Korea Convergence Society, 9(2), 7-12. https://doi.org/10.15207/JKCS.2018.9.2.007
  13. L. L. Takacs. (1985). A two-step scheme for the advection equation with minimized dissipation and dispersion errors. Month Weather Rev, 113, 1050-1065. https://doi.org/10.1175/1520-0493(1985)113<1050:ATSSFT>2.0.CO;2
  14. J. A. Carrillo & F. Veci. (2007). Nonoscillatory interpolation methods applied to Vlasov-Based models. SIAM Journal on Scientific Computing, 29(3), 1179-1206. https://doi.org/10.1137/050644549
  15. C. W. Shu. (2009). High order weighted essentially non-oscillatory schemes for convection dominated problems, SIAM Review, 51, 82-126. https://doi.org/10.1137/070679065
  16. C. W. Shu & S. Osher. (1988). Efficient implementation of essentially non-oscillatory shock capturing schemes. Journal of Computational Physics, 77(2), 439-471. https://doi.org/10.1016/0021-9991(88)90177-5
  17. J. M. Qui & A. Christlieb. (2010). A Conservative high order semi-Lagrangian WENO method for the Vlasov equation, Journal of Computational Physics, 229, 1130-1149. https://doi.org/10.1016/j.jcp.2009.10.016
  18. D. K. Yi & J. E. Park. (2015). Comparative analysis methods for digital simulation. Journal of Digital Convergence, 13(9), 209-218. https://doi.org/10.14400/JDC.2015.13.9.209