KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Human Visual System-aware Dimming Method Combining Pixel Compensation and Histogram Specification for TFT-LCDs

  • Jin, Jeong-Chan (Department of Electrical and Computer Engineering, Ajou University) ;
  • Kim, Young-Jin (Department of Electrical and Computer Engineering, Ajou University)
  • Received : 2016.11.18
  • Accepted : 2017.08.09
  • Published : 2017.12.31
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Abstract

In thin-film transistor liquid-crystal displays (TFT-LCDs), which are most commonly used in mobile devices, the backlight accounts for about 70% of the power consumption. Therefore, most low-power-related studies focus on realizing power savings through backlight dimming. Image compensation is performed to mitigate the visual distortion caused by the backlight dimming. Therefore, popular techniques include pixel compensation for brightness recovery and contrast enhancement, such as histogram equalization. However, existing pixel compensation techniques often have limitations with respect to blur owing to the pixel saturation phenomenon, or because contrast enhancement cannot adequately satisfy the human visual system (HVS). To overcome these, in this study, we propose a novel dimming technique to achieve both power saving and HVS-awareness by combining the pixel compensation and histogram specifications, which convert the original cumulative density function (CDF) by designing and using the desired CDF of an image. Because the process of obtaining the desired CDF is customized to consider image characteristics, histogram specification is found to achieve better HVS-awareness than histogram equalization. For the experiments, we employ the LIVE image database, and we use the structural similarity (SSIM) index to measure the degree of visual satisfaction. The experimental results show that the proposed technique achieves up to 15.9% increase in the SSIM index compared with existing dimming techniques that use pixel compensation and histogram equalization in the case of the same low-power ratio. Further, the results indicate that it achieves improved HVS-awareness and increased power saving concurrently compared with previous techniques.

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References

  1. A. Carroll and H. Gernot, "An analysis of power consumption in a smartphone," in Proc. of USENIX annual technical conference, vol. 14, June 23-25, 2010. https://www.usenix.org/legacy/event/usenix10/tech/full_papers/Carroll.pdf
  2. S. Kang, "SSIM preservation-based backlight dimming," Journal of Display Technology, vol. 10, pp.247-250, January, 2014. https://doi.org/10.1109/JDT.2014.2302299
  3. J. Chen, B. Ma, R. Li, T. Xia, and H. Cao. "Image dimming perceptual model based pixel compensation and backlight adjustment," Journal of Display Technology, Vol. 11, no. 9, pp. 744-752. 2015. https://doi.org/10.1109/JDT.2015.2436403
  4. Z. Wang, A.C.Bovik, H.R.Sheikh and E.P.Simoncelli, "Image quality assessment: from error visibility to structural similarity," IEEE Trans. on Image Processing, vol. 13, no. 4, pp.600-612, April, 2004. https://doi.org/10.1109/TIP.2003.819861
  5. C. Jung and Z. Xia, "Perceptual backlight scaling for low power liquid crystal displays based on visual saliency," in Proc. of the IEEE International Conference on Image Processing (ICIP), September 27-30, 2015.
  6. S. Kang and Y. Kim, "Segmentation-based clipped error control algorithm for global backlight dimming," Journal of Display Technology, vol 10, pp.568-573, July, 2014. https://doi.org/10.1109/JDT.2014.2311820
  7. Y. Li, P. Chu, J. Liu, and S. Du, "A novel partitioned light guide backlight LCD for mobile devices and local dimming method with nonuniform backlight compensation," Journal of Display Technology, Vol. 10, no. 4, pp. 321-328. 2014. https://doi.org/10.1109/JDT.2013.2296593
  8. C. Shen, Z. Lu, Y. Hung and S. Pei, "Visual enhancement using sparsity-based image decomposition for low backlight displays," in Proc. of 2016 IEEE International Symposium Circuits and Systems (ISCAS), August, 2016.
  9. J. Kim, K, Lee, J. Bae, J. Kim, and H. Kim, "Measurement of contrast reduction and its application to LCD backlight control," in Proc. of 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE), pp. 294-297, 2015.
  10. R. Gonzalez and R. E. Woods, Digital Image Processing, 3rd edition, Pearson, 2007.
  11. A. Iranli, H. Fatemi and M, Pedram, "HEBS: histogram equalization for backlight scaling," in Proc. of Design, Automation and Test in Europe, pp 346-351, March 7-11, 2005.
  12. W. C. Cheng and M. Pedram, "Power minimization in a backlit TFT-LCD by concurrent brightness and contrast scaling," in Proc. of the conference on Design, automation and test in Europe, vol. 1, Feb 16-20, 2004. http://dl.acm.org/citation.cfm?id=969038
  13. C. Lee, J. Kim, C. Lee and C. Kim, "Optimized brightness compensation and contrast enhancement for transmissive liquid crystal displays," IEEE Trans. on Image Processing on Circuits and Systems for Video Technology, Vol. 24, no. 4, pp. 576-590, April, 2014. https://doi.org/10.1109/TCSVT.2013.2276154
  14. C. Jung, and L. Wang, "Power-constrained backlight scaling using brightness compensated contrast-tone mapping operation," Visual Communications and Image Processing (VCIP), pp. 1-4, 2015.
  15. Y. Kim, "Contrast enhancement using brightness preserving bi-histogram equalization," IEEE Trans. Consumer Electronics, vol. 43, pp.1-8, February, 1997. https://doi.org/10.1109/30.580378
  16. Y. Q. Wang, B. Chen and M. Zhang, "Image enhancement based on equal area dualistic sub-image histogram equalization method," IEEE Trans. on Consumer Electronics, vol. 45, pp. 68-75, February, 1999. https://doi.org/10.1109/30.754419
  17. T. Arici and S. Dikbas, "A histogram modification framework and its application for image contrast enhancement," IEEE Trans.on Image Processing, vol.18, pp.1921-1935, September, 2009. https://doi.org/10.1109/TIP.2009.2021548
  18. H. R. Sheikh, Z. Wang, and A. C. Bovik, "A statistical evaluation of recent full reference image quality assessment algorithms," IEEE Trans. on Image Processing, vol. 15, no. 11, pp. 3440-3451, November, 2006. https://doi.org/10.1109/TIP.2006.881959