대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

다중 컬러필터 조리개 시스템을 위한 적응적 히스토그램 평활화를 이용한 영상 개선

Image Enhancement Using Adaptive Region-based Histogram Equalization for Multiple Color-Filter Aperture System

  • 이은성 (중앙대학교 첨단영상대학원) ;
  • 강원석 (중앙대학교 첨단영상대학원) ;
  • 김상진 (중앙대학교 첨단영상대학원) ;
  • 백준기 (중앙대학교 첨단영상대학원)
  • Lee, Eun-Sung (Dept. of Image Engineering. Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University) ;
  • Kang, Won-Seok (Dept. of Image Engineering. Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University) ;
  • Kim, Sang-Jin (Dept. of Image Engineering. Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University) ;
  • Paik, Joon-Ki (Dept. of Image Engineering. Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
  • 투고 : 2010.08.27
  • 심사 : 2010.12.01
  • 발행 : 2011.03.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문은 다중 컬러 필터 조리개 (multiple color-filter aperture; MCA) 시스템에서 영역 적응적 히스토그램 평활화를 사용하여 저노출 환경에서도 강건한 새로운 디지털 다중초점 (multifocusing) 방법을 소개한다. MCA 시스템은 획득된 영상의 컬러 채널 간에 발생하는 부정합 (misalignment) 정도를 측정하여 카메라의 거리에 따른 장면의 상대적 심도 정보를 추출한다. 추출된 상대적 심도 정보는 관심영역 (regsion-of-interests; ROIs) 분류 (classification), 정합 (registration), 융합 (fusion) 등의 과정을 통하여 다중초점 영상을 생성한다. 그러나 MCA 시스템은 유한한 구경의 조리개로 때문에 저노출 환경에서 성능의 저하를 초래하게 된다. 이러한 문제를 해결하기 위해 공간 적응적 히스토그램 확장을 이용한다. 실험결과에서 볼 수 있듯이, 제안한 기술은 저노출 환경에서도 콘트라스트가 향상된 다중초점 영상을 복원할 수 있음을 보여준다.

In this paper, we present a novel digital multifocusing approach using adaptive region-based histogram equalization for the multiple color-filter aperture (MCA) system with insufficient amount of incoming light. From the image acquired by the MCA system, we can estimate the depth information of objects at different distances by measuring the amount of misalignment among the RGB color planes. The estimated depth information is used to obtain multifocused images together with the process of the region-of-interests (ROIs) classification, registration, and fusion. However, the MCA system results in the low-exposure problem because of the limited size of the apertures. For overcoming this problem, we propose adaptive region-based histogram equalization. Based on the experimental results, the proposed algorithm is proved to be able to obtain in-focused images under the low light level environment.

키워드

참고문헌

  1. V. Mike, D. Cho, D. Har, and J. Paik, "Color shift model-based segmentation and fusion for digital auto focusing," Journal of Imaging Science and Technology, vol. 51, no. 4, pp. 368-379, July/August 2007. https://doi.org/10.2352/J.ImagingSci.Technol.(2007)51:4(368)
  2. Y. Bando, B. Chen, and T. Nishita, "Extracting depth and matte using a color-filtered aperture," ACM Trans on Graphics, vol. 27, no. 5, pp. 134:1-134:9, December 2008.
  3. E. Lee, W. Kang, S. Kim and J. Paik, "Color shift model-based image enhancement for digital multifocusing based on a multiple color-Filter aperture camera," IEEE Trans on Consumer Electronics, vol. 56, no. 2, pp. 317-323, May 2010. https://doi.org/10.1109/TCE.2010.5505934
  4. J. Shin, V. Maik, J. Lee, and J. Paik, "Multi-object digital auto-focusing using image fusion," Proc. ACIVS 2005, LNCS, vol. 3708, pp. 806-813, September 2005.
  5. V. Maik, J. Shin, J. Lee, and J. Paik, "Pattern selective image fusion for multi-focus image reconstruction," Proc. CAIP 2005, LNCS, vol. 3691, pp. 677-684, September 2005.
  6. J. Shin, S. Hwang, S. Lee, and J. Paik, "Isotropic blur identification for fully digital auto-focusing," Proc. ICIAR 2005, LNCS, vol. 3656, pp. 125-132, September 2005.
  7. S. Nayar, "Computational cameras: redefining the image," IEEE Computer Magazine, Special Issue on Computational Photography, pp.30-38, August, 2006.
  8. G. Park, H. Cho and M. Choi, "A contrast enhancement method using dynamic range separate histogram equalization," IEEE Trans on Consumer Electronics, vol. 54, no. 4, pp. 1981-1987, October 2008. https://doi.org/10.1109/TCE.2008.4711262
  9. C. Sun, S. Ruan, M. Shie, and T. Pai, " Dynamic contrast enhancement based on histogram specification," IEEE Trans on Consumer Electronics, vol. 51, no. 4, pp. 1300- 1305, November 2005. https://doi.org/10.1109/TCE.2005.1561859
  10. E. Castro and C. Morandi "Registration of translated and rotated images using finite fourier transforms," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 5, pp. 700-703, September 1987.
  11. R. Achanta, F. J. Estrada, P. Wils, and S. Susstrunk, "Salient region detection and segmentation," in Proc. ICVS, vol. 5008, pp. 66-75, May 2008.
  12. R. Gonzalez and R. Woods, Digital Image Processing, 3rd ed., PrenticeHall, 2007.