균일한 도트 분포를 위한 문턱값 변조 오차확산 방법

A Threshold Modulated Error Diffusion Method for Homogeneous Dot Distributions

  • 발행 : 2000.07.25

초록

디지털 영상 출력 장치를 위해 연속 계조 영상을 이진 영상으로 변환하는 오차확산 방법은 사람의 시각 특성에 적합한 고주파 성분의 이진 영상을 만들어 내지만 균일하지 못한 점의 분포로 인해 영상의 화질을 저하시키는 패턴이 발생하게 된다. 이러한 단점을 해결하기 위해 다양하게 개선된 오차확산 방법들이 제안되었다. 본 논문에서는 우선 오차확산 방법이 균일한 점의 분포를 발생시키지 못하는 원인을 분석하고 주기함수를 이용하여 이진 문턱값을 조절함으로서 이진 영상의 점의 분포를 균일하게 하여 화질을 향상시키는 방법을 제안한다. 제안하는 방법은 이진 영상의 화질을 결정하는 소수 화소(minor pixels)가 주어진 계조에 따라 일정한 주거리(principal distance)를 갖도록 하여 이진 화소의 뭉침 현상이나 공백 현상을 최소화 하고 균일한 분포를 갖도록 한다.

The error diffusion technique is frequently utilized for the digital Imaging output devices to convert continuous level Image into bi-level Image It Yields the binary image with the high frequency emphasis that gives a pleasing perception to human eyes But, due to the non-homogeneous distribution of dots, It exhibits undesirable patterns that degenerate the perceived quality Various techniques have been proposed to Improve the Image quality by the error diffusion techniques In this paper, the cause of non-homogeneity of dot distribution is analyzed first. A threshold modulation technique that employs a simple sinusoidal function is proposed in this paper The proposed method achieves the homogeneous dot distribution by forcing the minor pixels on the binary Image to maintain the principal distance defined according to their gray levels. It also minimizes the void and clusters of minor pixels.

키워드

참고문헌

  1. R. A. Ulichiney, Digital Halftoning, MIT Press, 1987
  2. R. W. Floyd and L Steinberg, 'An adaptIve algorithm for spatial grey-scale,' Proc Soc. Inf. Disp 17, pp 75-77, 1976
  3. J. Sullivan, L Ray and R. Miller, 'Design of Minimum Visual Modulation Halftone Patterns,' IEEE Trans. on System, Man and Cybernetics Vol 21 No.1, pp. 34-39, Jan,/Feb. 1991 https://doi.org/10.1109/21.101134
  4. P W Wong, Error Diffusion With Dynamically Adjusted Kernel, IEEE Int. Conf. on ASSP, pp. V.113- V116, April 1994 https://doi.org/10.1109/ICASSP.1994.389435
  5. K. M. Kang, S. W Kang, and C. W. Kim, 'A modified error diffusion scheme based on the human visual model,' Recent Progress in Digital Halftoning II, SPIE, pp. 30-34 1999
  6. S. Kollias and D Anastassiou, 'A unified neural network approach to digital image halftoning,' IEEE Tans on Signal Processing, Vol 39, No.4, pp 980-984, 1991 https://doi.org/10.1109/78.80930
  7. S. H. Park, K. M. Kang, and C. W Kim, 'Estimation of error diffusion kernel using genetic algorithm,' SPIE Vol. 3300, pp. 330-340, 1998 https://doi.org/10.1117/12.298296
  8. K. M. Kang and C. W. Kim, 'A non-causal error diffusion method for edge enhancement,' SPIE Vol. 3018, pp. 255-265, 1997 https://doi.org/10.1117/12.271599
  9. Z. Fan, 'Error Diffusion with a More Symmetric Error Distribution,' SPIE Vol. 2179, pp. 150-158, 1994 https://doi.org/10.1117/12.172666
  10. K. T. Knox, 'Error image in error diffusion,' SPIE Vol. 1657, pp. 168-179, 1992 https://doi.org/10.1117/12.58334
  11. J. N. Shiau and Z. Fan, 'A Set of easily Implementable Coefficients in Error Diffusion with Reduced Worm Artifacts.' SPIE Vol. 2658, pp. 222-225, 1996 https://doi.org/10.1117/12.236968
  12. T Mitsa and K. J. Parker, ' Digital halftoning technique using a blue noise mask,' Proc. of IEEE Int. Conf Commun , pp. 26-1126-15, 1997
  13. R. A. Ulichney, 'The void-and-cluster method for dither array generation,' SPIE Vol 1913, pp 332-343, 1993 https://doi.org/10.1117/12.152707
  14. R. Eschbach and K. T Knox, 'Error diffusion algorithm with edge enhancement,' J. of Opt Sac Am.A, Vol.8, No 12, pp 1844-1850, Dec, 1991
  15. R. Eschbach, 'Error diffusion algorithm with homogeneous response in highlight and shadow areas,' J. of Electronic Imaging 6(3), pp 348-356, 1997 https://doi.org/10.1117/12.272655
  16. D. U. Hong and C. W. Kim, 'A serpentine error diffusion kernel with threshold modulation for homogeneous dot,' PPIC/JH'98, pp. 363-366, 1998