Abstract
This paper proposes a new auto-exposure and auto white-balance algorithm that can accurately detect high-contrast lighting conditions and improve the dynamic range of output images for a camera system. The proposed method calculates the difference between the mean value and the median value of the brightness level of captured pictures to estimate lighting conditions. After that, a multiple exposure mechanism which can improve image details is carried out in combination with a simple auto white-balance algorithm which is capable of detecting pictures with one primary color. Simulation results show that the system works well with CMOS sensors used in mobile phones and surveillance cameras. Besides, the proposed algorithm is fast and simple and therefore can be fitted in most CMOS platforms that have limited capabilities.
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J. Y. Liang, Y. J. Qin, and Z. L. Hong, “An auto-exposure algorithm for detecting high contrast lighting conditions,” Proc. of the 7th Int. Conf. on ASIC, Guilin, Peoples R. China, vols. 1 and 2, pp. 725–728, Oct. 2007.
S. Shimizu, T. Kondo, T. Kohashi, M. Tsuruta, and T. Komuro, “A new algorithm for exposure control based on fuzzy logic for video cameras,” IEEE Trans. Consum. Electron., vol. 38, pp. 617–623, Aug. 1992.
M. Murakami and N. Honda, “An exposure control system of video cameras based on fuzzy logic using color information,” Proc. of the 5th IEEE Int. Conf. on Fuzzy Systems, Los Angeles, CA, vols. 1–3, pp. 2181–2187, Sept. 1996.
J. S. Lee, Y. Y. Jung, B. S. Kim, and S. J. Ko, “An advanced video camera system with robust AF, AE, and AWB control,” IEEE Trans. Consum. Electron., vol. 47, pp. 694–699, Aug. 2001.
W. C. Kao, C. C. Hsu, C. C. Kao, and S. H. Chen, “Adaptive exposure control and real-time image fusion for surveillance systems,” Proc. of IEEE Int. Symp. on Circuits and Systems, Kos, Greece, vols. 1–11, pp. 935–938, May 2006.
J. Y. Huo, Y. L. Chang, J. Wang, and X. X. Wei, “Robust automatic white balance algorithm using gray color points in images,” IEEE Trans. Consum. Electron., vol. 52, pp. 541–546, May 2006.
Y. Kim, J. S. Lee, A. W. Morales, and S. J. Ko, “A video camera system with enhanced zoom tracking and auto white balance,” IEEE Trans. Consum. Electron., vol. 48, pp. 428–434, Aug. 2002.
Y. C. Liu, W. H. Chan, and Y. Q. Chen, “Automatic white balance for digital still camera,” IEEE Trans. Consum. Electron., vol. 41, pp. 460–466, Aug. 1995.
N. Nakano, R. Nishimura, H. Sai, A. Nishizawa, and H. Komatsu, “Digital still camera system for megapixel CCD,” IEEE Trans. Consum. Electron., vol. 44, pp. 581–586, Aug. 1998.
B. Hu, Q. Lin, X. L. Kang, and G. M. Chen, “A new algorithm for automatic white balance with priori,” IEEE Asia-Pacific Conf. on Circuits and Systems, Tianjin, Peoples R. China, pp. 109–112, Dec. 2000.
T. Kuno, H. Sugiura, and M. Atoka, “A new automatic exposure system for digital still cameras,” IEEE Trans. Consum. Electron., vol. 44, pp. 192–199, Feb. 1998.
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Vuong, Q.K., Yun, SH., Kim, S. (2010). A New Robust Combined Method for Auto Exposure and Auto White-Balance. In: Amouzegar, M. (eds) Advances in Machine Learning and Data Analysis. Lecture Notes in Electrical Engineering, vol 48. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3177-8_11
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DOI: https://doi.org/10.1007/978-90-481-3177-8_11
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