An Efficient Vehicle Image Compensation Algorithm based on Histogram Equalization

히스토그램 균등화 기반의 효율적인 차량용 영상 보정 알고리즘

  • Received : 2014.10.30
  • Accepted : 2015.03.12
  • Published : 2015.03.31


In this paper, we propose an efficient vehicle image compensation algorithm based on Histogram Equalization. The proposed a vehicle image compensation algorithm was elimination to the vehicle image shake using motion compensation and motion estimation. And, algorithm was calculated the histogram of pixel values from each sub-image by dividing the image as the constant size areas in order to image enhancement. Also, it had enhancement to the image by adjusting the gradient. The proposed algorithm was evaluate the difference between of performance and time, image by applied to the IP, and were confirmed the image enhancement with removing of vehicle camera image shake. In this paper, the proposed vehicle image enhancement algorithm was demonstrated effectiveness when compared to existing vehicle image stabilization, because the elimination of shake for the vehicle images used real-time processing without using a memory. And it was obtained the reduction effect of the computation time by the calculated through block matching, and obtained the better restoration result for naturalness of the image with the lowest noise.


  1. S.Y Tak, J.M Ban, S Lew, W.J Lee, B.R Lee and H.C Kang, "A Study on an Image Stabilization in Moving Vehicle" Journal of The Institute of Electronics Engineers, vol. 49, SP no 4, pp.95-104, Jul 2012.
  2. S.Y Kim, G.K Kang, Y.W Ryu, S.Y Oh, K.S Kim, S.C Park, and J.W Kim, "Intelligent Driver Assistance Systems based on All-Around Sensing", IEIE, Journal of IEIE (TC), Vol 43, No. 9, pp49-59, Sept. 2006.
  3. Lucas, B. & Kanade, T., "An iterative image registration technique with an application to stereo vision", Proceeding DARPA Image Understanding Workshop, pp121-130, Apr. 1981.
  4. A. Karpenko, D. Jacobs, J. Baek, and M. Levoy, "Digital Video Stabilization and Rolling Shutter Correction using Gyroscopes", Stanford Tech Report CTSR 2011-03, pp1-7, Mar. 2011.
  5. A. Amanatiadis, A. Gasteratos, S. Papadakis, and V. Kaburlasos, "Image Stabilization in Active Robot Vision", INTECH, Robot Vision, pp261-274, Mar. 2010.
  6. M. Drahansky, F. Orsag, and P. Hanacek, "Accelerometer Based Digital Video Stabilization for General Security Surveillance Systems", International Journal of Security and Its Applications, Vol. 4, No. 1, pp1-10, Jan. 2010.
  7. T. Kondo, W. Kongprawechnon, "A matching technique using gradient orientation patterns", Thammasat Int. J. Sc. Tech., Vol. 14, No. 3, pp41-55, Sept. 2009.
  8. J.H. Shin, S.B. Jang, and I.H. Jee, "Introduction of Digital Image Process", Hanhit media, Jan. 2008
  9. W. Cho, D. Kim, and K. Hong, "CMOS digital image stabilization," IEEE Transactions on Consumer Electronics, Vol. 53, No. 3, pp. 979-986, Aug. 2007. DOI:
  10. C. W. Chiu, P. C. P. Chao, and D. Y. Wu, "Optimal design of magnetically actuated optical image stabilizer mechanism for cameras in mobile phones via genetic algorithm," IEEE Trans. on Magnetics, Vol. 6, No. 43, pp. 2582-2584, Jun. 2007. DOI:
  11. W. Cho, K. Hong, "Affine motion based CMOS distortion analysis and CMOS digital image stabilization," IEEE Trans. Consum. Electron., Vol. 53, No. 3, pp. 833- 841, Aug. 2007. DOI:
  12. A. Amanatiadis, I. Andreadis, "An integrated dynamic image stabilizer applied to zooming systems," in Proc. of the IEEE Instr. Meas. Technol. Conf., pp. 1-5, May. 2007.