S-CIELAB 색차를 이용한 개선된 혼합 블루 노이즈 마스크

Modified Jointly Blue Noise Mask Approach Using S-CIELAB Color Difference

  • 김윤태 (경북대학교 전자전기컴퓨터학부) ;
  • 조양호 (경북대학교 전자전기컴퓨터학부) ;
  • 이철희 (경운대학교 컴퓨터공학과) ;
  • 하영호 (경북대학교 전자전기컴퓨터학부)
  • 발행 : 2003.07.01

초록

본 논문은 디지털 칼라 하프토닝 방법으로써 S-CIELAB 색차를 이용한 개선된 혼합 블루노이즈 마스크 방법을 제안한다. 블루 노이즈 패턴의 눈에 거슬리는 패턴과 색차와의 관계를 조사하여 제안한 하프토닝 방법은 고화질의 블루노이즈 패턴을 유지하면서 색차를 줄이는 방법이다. 따라서, 색차를 줄이기 위해서 마스크 생성 과정에서 저주파 오차와 S-CIELAB 색차 모두가 고려되고, 단일 패턴과 결합 패턴에 대해서 계산하였다. 계산된 저주파 필터 오차를 사용하여 다중 이진 패턴으로부터 도트들을 더하거나 빼줌으로써 생성되며, 최종적으로 작은S-CIELAB 색차를 나타내는 패턴을 선택한다. 실험에서는 제안한 방법이 기존의 JBNM 방법보다 작은 색차를 나타내면서 인간 시각에는 보기 좋은 하프토닝 영상을 생성한다는 것을 확인할 수 있었다.

This paper proposes a modified jointly-blue noise mask (MJBNM) method using the S-CIELAB color measure as digital color halftoning method. Based on an investigation of the relation between the pattern visibility and the chromatic error, of a blue noise pattern, a halftoning method is proposed that reduces the chromatic error, while preserving a high quality blue noise pattern. Accordingly, to reduce the chrominance error, the low-pass filtered error and S-CIELAB chrominance error are both considered during the mask generation procedure and calculated for single and combined patterns. Using the calculated low-pass filtered error, the patterns are then updated by either adding or removing dots from the multiple binary patterns. Finally, the pattern exhibiting the lower S-CIELAB chrominance error is selected. Experimental results demonstrated that the proposed algorithm can produce a visually pleasing half toned image with a lower chrominance error than the JBNM method.

키워드

참고문헌

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