Journal of the Institute of Electronics Engineers of Korea SD (대한전자공학회논문지SD)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Mid frequency - DCT focus measure operator for the robust autofocus

노이즈에 둔감한 밴드패스 이산 코사인 초점 값 연산자

  • Published : 2006.12.25
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Abstract

This paper proposed noise insensitive 4*4 mid frequency-OCT (MF-DCT) focus measure operator. Proposed operator enhanced low power 8*8 MDCT operator to have 4*4 rotationally same form for Gaussian noise. MF-DCT operator acting like band-pass filter suppresses both low-frequency signal useless for focus measure and high-frequency signal affected by impulsive noise. Also it is proved to be linear because it uses the energy of band-pass filtered signal as focus measure. Experimental result shows its superiority by comparing AUM with traditional operators.

본 논문에서는 노이즈에 둔감한 4*4 밴드패스 이산 코사인 (MF-DCT) 초점 값 연산자를 제안하였다. 제안된 연산자는 DCT 결과 중 중간 주파수 성분을 사용하는 8*8 MDCT 연산자를 노이즈에 둔감하도록 4 형태로 개선한 것으로써 연산자를 180도 회전하여도 같은 구조를 같도록 하였다. 이 연산자는 샘플링 주파수의 절반 부분지 주파수를 통과시키는 밴드패스 필터와 같이 동작하여 초점 정보를 가지고 있지 않는 저주파 신호와 노이즈에 의해 많은 영향을 받는 고주파 신호를 억제함으로써 노이즈에 둔감한 특성을 가진다. 또한 밴드패스 필터를 통과한 성분의 에너지를 초점 값으로 사용함으로써 초점 합의 선형성을 보장받게 된다. 실험 결과에서는 MF-DCT 연산자의 가우시안 노이즈 및 임펄시브 노이즈 특성을 살펴보기 위해 기존의 초점 값 연산자들과의 Autofocusing Uncertain Measure (AUM)비교를 통해 우수성을 검증하였다.

Keywords

References

  1. S. M. Sohn, S. H. Yang, S. W. Kim, K H. Baek, and W. H. Paik, 'SoC design of an auto-focus driving image signal processor for mobile camera applications,' IEEE Trans. Consumer Electronics, vol. 52, no. 1, pp. 10-16, Feb. 2006 https://doi.org/10.1109/TCE.2006.1605018
  2. V. Peddigari, M. Gamadia, and N. Kehtarnavaz, 'Real-time implementation issues in passive automatic focusing for digital still cameras,' J. of Imaging Science and Technology, vol. 49, pp. 114-123, March/April 2005
  3. M. Subbarao, and J.K Tyan, 'Selecting the optimal focus measure for autofocusing and depth-from-focus,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 20, no. 8, pp. 864-870, Aug. 1998 https://doi.org/10.1109/34.709612
  4. E. Krotkov, 'Focusing,' Int. J. of Computer Vision, vol. 1, pp. 223-237, 1987 https://doi.org/10.1007/BF00127822
  5. M. Subbarao, and J.K Tyan, 'The optimal focus measure for passive autofocusing and depth from focus,' in SPIE Conf. Videometrics IV, vol. 2598, pp. 89-99, Philadelphia, Oct. 1995 https://doi.org/10.1117/12.220891
  6. S. Y. Lee, S. S. Park, C. S. Kim, Y. Kumar, and S. W. Kim, 'Low-power auto focus algorithm using. modified OCT for the mobile phones,' IEEE Int. Conf. on Consumer Electronics, pp. 67-68, Jan. 2006 https://doi.org/10.1109/ICCE.2006.1598313
  7. G. Yang, and B.J. Nelson, 'Wavelet-based autofocusing and unsupervised segmentation of microscopic images,' in IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, vol. 3, pp. 2143-2148, Oct. 2003 https://doi.org/10.1109/IROS.2003.1249188
  8. Z. G. Jiang, D. B. Han, J. Chen, and X. K Zhou, 'A Wavelet Based Algorithm for Multi-Focus Micro-Image Fusion,' in IEEE 3rd Int. Conf. Image and Graphics, Hong Kong, Dec. 2004, pp. 176-179 https://doi.org/10.1109/ICIG.2004.29
  9. J. M. Tenenbawn, 'Accommodation in computer vision,' Ph.D. thesis, Stanford University, 1970
  10. S. K Navar and Y. Nakagawa, 'Shape from focus,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 16, pp. 824-831, Aug. 1994 https://doi.org/10.1109/34.308479
  11. K. S. Choi, J. S. Lee, and S. J. Ko, 'New autofocus technique using the frequency selective weighted median filter for video cameras,' IEEE Trans. on Consumer Electronics, vol. 45, no. 3, pp. 820-827, Aug. 1999 https://doi.org/10.1109/30.793616