Research Article
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Year 2021, Volume: 9 Issue: 1, 55 - 65, 30.06.2021

Mohammed Albaba , Meryem Sena Akkuş

https://doi.org/10.51354/mjen.872956

Abstract

References

  • [1] S.-J. Kang, “Image-quality-based power control technique for organic light emitting diode displays,” J. Display Technol., vol. 11, no. 1, pp. 104–109, Jan. 2015.
  • [2] ALBABA, Mohammed; AKKUS, Meryem Sena. NEXT GENERATION DISPLAY TECHNOLOGY: TRANSPARENT ORGANIC LIGHT EMITTING DIODES. Selcuk-Teknik Dergisi, [S.l.], p. 168-180, dec. 2020. ISSN 1302-6178. Available at: http://sutod.selcuk.edu.tr/sutod/article/view/524. Date accessed: 29 Dec. 2020.
  • [3] C. Chae, H. Le, K. Lee, G. Cho, and G. Cho, “A single-inductor step-up DC–DC switching converter with bipolar outputs for active matrix OLED mobile display panels,” IEEE J. Solid-State Circuits, vol. 44, no. 2, pp. 509–524, Feb. 2009.
  • [4] C. Lee, C. Lee, Y.-Y. Lee, and C.-S. Kim, “Power-constrained contrast enhancement for emissive displays based on histogram equalization,” IEEE Trans. Image Process., vol. 21, no. 1, pp. 80–93, Jan. 2012.
  • [5] P. Chondro, C.-H. Chang, S.-J. Ruan, and C.-A. Shen, “Advanced multimedia power saving method using dynamic pixel dimmer on AMOLED Displays,” IEEE Trans. Circuits Syst. Video Technol., vol. 28, no. 9, Sep. 2017.
  • [6] A. Carroll and G. Heiser, “An analysis of power consumption in a smartphone,” in Proceedings of the USENIX Conference on USENIX Annual Technical Conference, vol. 14, p. 21, Boston, Mass, USA, June 2010.
  • [7] X. Chen, Y.Chen, Z.Ma, andF. C. A. Fernandes, “How is energy consumed in smartphone display applications?” in Proceedings of the 14th Workshop on Mobile Computing Systems and Applications (ACM HotMobile ’13), Jekyll Island, Georgia, USA, February 2013.
  • [8] L. Deguang, G. Bing, S. Yan, L. Junke, and H. Yanhui. Making Image More Energy Efficient for OLED Smart Devices. Hindawi Publishing Corporation, Mobile Information Systems, Volume 2016, Article ID 6575931, 8 pages. http://dx.doi.org/10.1155/2016/6575931
  • [9] M. Dong and L. Zhong, “Power modeling and optimization for OLED displays,” IEEE Transactions on Mobile Computing, vol. 11, no. 9, pp. 1587–1599, 2012.
  • [10] A. Laaperi, “Disruptive Factors in the OLED Business Ecosystem,” Information Display Magazine, vol. 25, pp. 8-13, Sept. 2009.
  • [11] S. Yong-Goo, P. Seung, Y. Yoon-Jae, Y. Min-Jae, and K. Sung-Jea. Unsupervised Deep Contrast Enhancement with Power Constraint for OLED Displays. This research was funded and supported by LG Display CO., Ltd.
  • [12] S. BoHum, K. Soontae. Enhancing Energy Efficiency on OLED Display Equipped Mobile Device.
  • [13] K. Zhang, W. Zuo, Y. Chen, D. Meng and L. Zhang, "Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising," IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3142-3155, 2017.
  • [14] O. Oktay et al. "Anatomically constrained neural networks (ACNNs): application to cardiac image enhancement and segmentation," IEEE transactions on medical imaging, 2017.
  • [15] Y.-O. Nam, D.-Y. Choi, and B. C. Song, “Power-constrained contrast enhancement algorithm using multiscale Retinex for OLED display,” IEEE Trans. Image Process., vol. 23, no. 8, pp. 3308–3320, Aug. 2014.
  • [16] D. J. Pagliari, E. Macii, and M. Poncino, “LAPSE: Low-Overhead Adaptive Power Saving and Contrast Enhancement for OLEDs,” IEEE Trans. Image Process, vol. 17, no. 9, 2018.
  • [17] P. Arbela´ez, M. Maire, C. Fowlkes, and J. Malik, “Contour detection and hierarchical image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 898-916, May 2011.
  • [18] F. Yu and V. Koltun, “Multi-scale context aggregation by dilated convo-lutions,” in Proc. Int. Conf. Learn. Representations, 2016.
  • [19] D. Chen, J. Liao, L. Yuan, N. Yu, and G. Hua, "Coherent online video style transfer," Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017.
  • [20] Z. Yi, H. Zhang, P. Tan, and M. Gong, "Dualgan: Unsupervised dual learning for image-to-image translation," Proceedings of the IEEE inter-national conference on computer vision (ICCV), 2017.
  • [21] D. Kinga and J. Ba, “Adam: A method for stochastic optimization,” Proc. Int. Conf. Learn. Represent. (ICLR), 2015.
  • [22] C. Lee, C. Lee, Y.-Y. Lee, and C.-S. Kim, “Power-constrained contrast enhancement for emissive displays based on histogram equalization,” IEEE Trans. Image Process., vol. 21, no. 1, pp. 80–93, Jan. 2012.
  • [23] L. Ding andA.Goshtasby, “On the canny edge detector,” Pattern Recognition, vol. 34, no. 3, pp. 721–725, 2001.
  • [24] T. K.Wee andR. K. Balan, “Adaptive display power management for OLED displays,” in Proceedings of the 1st ACM SIGCOMM Workshop on Mobile Gaming (MobiGames ’12), pp. 25–30, Helsinki, Finland, August 2012.
  • [25] X. Chen, Y. Chen, and C. J. Xue, “DaTuM: dynamic tone mapping technique for OLED display power saving based on video classification,” in Proceedings of the 52nd ACM/EDAC/IEEE Design Automation Conference (DAC ’15), pp. 1–6, IEEE, San Francisco, Calif, USA, June 2015.
  • [26] M. Dong et al., “Power Modeling of Graphical User Interfaces on OLED Displays,” Proc. ACM/IEEE Design Automation Conf. (DAC), June 2009.
  • [27] M. Dong, L. Zhong. Chameleon: A Color-Adaptive Web Browser for Mobile OLED Displays. MobiSys 2011. The Ninth International Conference on Mobile Systems, Applications, and Services. June 28th - July 1st, 2011. Washington, DC, USA. https://www.sigmobile.org/mobisys/2011/program.html
  • [28] J. Yu, H. Han, H. Zhu, Y. Chen, J. Yang, Y. Zhu, G. Xue, and M. Li, “Sensing human-screen interaction for energy-efficient frame rate adaptation on smartphones,” IEEE Transactions on Mobile Computing, vol. 14, no. 8, pp. 1698–1711, 2015.
  • [29] A. Developers. Hardware acceleration. [Online]. Available: https://developer.android.com/guide/topics/graphics/hardware-accel.html Date accessed: 19 Nov. 2020
  • [30] X. Chen, J. Zeng, Y. Chen, W. Zhang, and H. Li, “Fine-grained dynamic voltage scaling on oled display,” in Design Automation Conference (ASP-DAC), 2012 17th Asia and South Pacific. IEEE, 2012, pp. 807–812.
  • [31] X. Chen, J. Zheng, Y. Chen, M. Zhao, and C. J. Xue, “Quality-retaining oled dynamic voltage scaling for video streaming applications on mobile devices,” in Proceedings of the 49th Annual Design Automation Conference. ACM, 2012, pp. 1000–1005.
  • [32] B.-H. Lee and Y.-J. Kim, “Dynamic voltage scaling using scene change detection for video playback on mobile amoled displays,” in Proceedings of the 2016 International Symposium on Low Power Electronics and Design. ACM, 2016, pp. 302–307.
  • [33] T.-C. Chang, S. S.-D. Xu, and S.-F. Su, “SSIM-based quality-on-demand energy-saving schemes for OLED displays,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 46, no. 5, pp. 623–635, May 2016.
  • [34] Berkeley, University of California. Computer Vision Group. Contour Detection and Image Segmentation Resources. Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500). Contour Detection and Hierarchical Image Segmentation. P. Arbelaez, M. Maire, C. Fowlkes and J. Malik. IEEE TPAMI, Vol. 33, No. 5, pp. 898-916, May 2011. https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html

Technologies based on energy savings for OLED devices

Year 2021, Volume: 9 Issue: 1, 55 - 65, 30.06.2021

Mohammed Albaba , Meryem Sena Akkuş

https://doi.org/10.51354/mjen.872956

Abstract

Recently, scientists are paying more attention to the Organic Light Emitting Diode (OLED) technology as it is being used in devices and displays to play videos and show photos with high resolution. This technology is used in products such as mobile phones, televisions, laptops, etc. To make the energy consumed less, new methods were shown up to prevent high energy consumption while presenting videos and photos on OLED devices and displays without losing their details and quality, one of the methods is a deep learning-based technique which is related to artificial intelligence. In this review paper, the last methods were discussed as well as their results. Saturation, brightness, contrast, and luminance are factors that impacting energy consumption. In terms of OLED mobile phones, there were a few studies that concentrated on turning off the unnecessary pixels which will be black as default, and as a result, the lifetime of batteries will be extended. Also, for OLED mobile phones, a web browser called Chameleon was presented as it has some modes to save the energy consumed while surfing the internet by remapping the displayed colors of the website.

Keywords

OLED Displays Power Consumption Deep Learning Method Chameleon Web Browser Reducing Power

References

  • [1] S.-J. Kang, “Image-quality-based power control technique for organic light emitting diode displays,” J. Display Technol., vol. 11, no. 1, pp. 104–109, Jan. 2015.
  • [2] ALBABA, Mohammed; AKKUS, Meryem Sena. NEXT GENERATION DISPLAY TECHNOLOGY: TRANSPARENT ORGANIC LIGHT EMITTING DIODES. Selcuk-Teknik Dergisi, [S.l.], p. 168-180, dec. 2020. ISSN 1302-6178. Available at: http://sutod.selcuk.edu.tr/sutod/article/view/524. Date accessed: 29 Dec. 2020.
  • [3] C. Chae, H. Le, K. Lee, G. Cho, and G. Cho, “A single-inductor step-up DC–DC switching converter with bipolar outputs for active matrix OLED mobile display panels,” IEEE J. Solid-State Circuits, vol. 44, no. 2, pp. 509–524, Feb. 2009.
  • [4] C. Lee, C. Lee, Y.-Y. Lee, and C.-S. Kim, “Power-constrained contrast enhancement for emissive displays based on histogram equalization,” IEEE Trans. Image Process., vol. 21, no. 1, pp. 80–93, Jan. 2012.
  • [5] P. Chondro, C.-H. Chang, S.-J. Ruan, and C.-A. Shen, “Advanced multimedia power saving method using dynamic pixel dimmer on AMOLED Displays,” IEEE Trans. Circuits Syst. Video Technol., vol. 28, no. 9, Sep. 2017.
  • [6] A. Carroll and G. Heiser, “An analysis of power consumption in a smartphone,” in Proceedings of the USENIX Conference on USENIX Annual Technical Conference, vol. 14, p. 21, Boston, Mass, USA, June 2010.
  • [7] X. Chen, Y.Chen, Z.Ma, andF. C. A. Fernandes, “How is energy consumed in smartphone display applications?” in Proceedings of the 14th Workshop on Mobile Computing Systems and Applications (ACM HotMobile ’13), Jekyll Island, Georgia, USA, February 2013.
  • [8] L. Deguang, G. Bing, S. Yan, L. Junke, and H. Yanhui. Making Image More Energy Efficient for OLED Smart Devices. Hindawi Publishing Corporation, Mobile Information Systems, Volume 2016, Article ID 6575931, 8 pages. http://dx.doi.org/10.1155/2016/6575931
  • [9] M. Dong and L. Zhong, “Power modeling and optimization for OLED displays,” IEEE Transactions on Mobile Computing, vol. 11, no. 9, pp. 1587–1599, 2012.
  • [10] A. Laaperi, “Disruptive Factors in the OLED Business Ecosystem,” Information Display Magazine, vol. 25, pp. 8-13, Sept. 2009.
  • [11] S. Yong-Goo, P. Seung, Y. Yoon-Jae, Y. Min-Jae, and K. Sung-Jea. Unsupervised Deep Contrast Enhancement with Power Constraint for OLED Displays. This research was funded and supported by LG Display CO., Ltd.
  • [12] S. BoHum, K. Soontae. Enhancing Energy Efficiency on OLED Display Equipped Mobile Device.
  • [13] K. Zhang, W. Zuo, Y. Chen, D. Meng and L. Zhang, "Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising," IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3142-3155, 2017.
  • [14] O. Oktay et al. "Anatomically constrained neural networks (ACNNs): application to cardiac image enhancement and segmentation," IEEE transactions on medical imaging, 2017.
  • [15] Y.-O. Nam, D.-Y. Choi, and B. C. Song, “Power-constrained contrast enhancement algorithm using multiscale Retinex for OLED display,” IEEE Trans. Image Process., vol. 23, no. 8, pp. 3308–3320, Aug. 2014.
  • [16] D. J. Pagliari, E. Macii, and M. Poncino, “LAPSE: Low-Overhead Adaptive Power Saving and Contrast Enhancement for OLEDs,” IEEE Trans. Image Process, vol. 17, no. 9, 2018.
  • [17] P. Arbela´ez, M. Maire, C. Fowlkes, and J. Malik, “Contour detection and hierarchical image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 898-916, May 2011.
  • [18] F. Yu and V. Koltun, “Multi-scale context aggregation by dilated convo-lutions,” in Proc. Int. Conf. Learn. Representations, 2016.
  • [19] D. Chen, J. Liao, L. Yuan, N. Yu, and G. Hua, "Coherent online video style transfer," Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017.
  • [20] Z. Yi, H. Zhang, P. Tan, and M. Gong, "Dualgan: Unsupervised dual learning for image-to-image translation," Proceedings of the IEEE inter-national conference on computer vision (ICCV), 2017.
  • [21] D. Kinga and J. Ba, “Adam: A method for stochastic optimization,” Proc. Int. Conf. Learn. Represent. (ICLR), 2015.
  • [22] C. Lee, C. Lee, Y.-Y. Lee, and C.-S. Kim, “Power-constrained contrast enhancement for emissive displays based on histogram equalization,” IEEE Trans. Image Process., vol. 21, no. 1, pp. 80–93, Jan. 2012.
  • [23] L. Ding andA.Goshtasby, “On the canny edge detector,” Pattern Recognition, vol. 34, no. 3, pp. 721–725, 2001.
  • [24] T. K.Wee andR. K. Balan, “Adaptive display power management for OLED displays,” in Proceedings of the 1st ACM SIGCOMM Workshop on Mobile Gaming (MobiGames ’12), pp. 25–30, Helsinki, Finland, August 2012.
  • [25] X. Chen, Y. Chen, and C. J. Xue, “DaTuM: dynamic tone mapping technique for OLED display power saving based on video classification,” in Proceedings of the 52nd ACM/EDAC/IEEE Design Automation Conference (DAC ’15), pp. 1–6, IEEE, San Francisco, Calif, USA, June 2015.
  • [26] M. Dong et al., “Power Modeling of Graphical User Interfaces on OLED Displays,” Proc. ACM/IEEE Design Automation Conf. (DAC), June 2009.
  • [27] M. Dong, L. Zhong. Chameleon: A Color-Adaptive Web Browser for Mobile OLED Displays. MobiSys 2011. The Ninth International Conference on Mobile Systems, Applications, and Services. June 28th - July 1st, 2011. Washington, DC, USA. https://www.sigmobile.org/mobisys/2011/program.html
  • [28] J. Yu, H. Han, H. Zhu, Y. Chen, J. Yang, Y. Zhu, G. Xue, and M. Li, “Sensing human-screen interaction for energy-efficient frame rate adaptation on smartphones,” IEEE Transactions on Mobile Computing, vol. 14, no. 8, pp. 1698–1711, 2015.
  • [29] A. Developers. Hardware acceleration. [Online]. Available: https://developer.android.com/guide/topics/graphics/hardware-accel.html Date accessed: 19 Nov. 2020
  • [30] X. Chen, J. Zeng, Y. Chen, W. Zhang, and H. Li, “Fine-grained dynamic voltage scaling on oled display,” in Design Automation Conference (ASP-DAC), 2012 17th Asia and South Pacific. IEEE, 2012, pp. 807–812.
  • [31] X. Chen, J. Zheng, Y. Chen, M. Zhao, and C. J. Xue, “Quality-retaining oled dynamic voltage scaling for video streaming applications on mobile devices,” in Proceedings of the 49th Annual Design Automation Conference. ACM, 2012, pp. 1000–1005.
  • [32] B.-H. Lee and Y.-J. Kim, “Dynamic voltage scaling using scene change detection for video playback on mobile amoled displays,” in Proceedings of the 2016 International Symposium on Low Power Electronics and Design. ACM, 2016, pp. 302–307.
  • [33] T.-C. Chang, S. S.-D. Xu, and S.-F. Su, “SSIM-based quality-on-demand energy-saving schemes for OLED displays,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 46, no. 5, pp. 623–635, May 2016.
  • [34] Berkeley, University of California. Computer Vision Group. Contour Detection and Image Segmentation Resources. Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500). Contour Detection and Hierarchical Image Segmentation. P. Arbelaez, M. Maire, C. Fowlkes and J. Malik. IEEE TPAMI, Vol. 33, No. 5, pp. 898-916, May 2011. https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html
There are 34 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Mohammed Albaba 0000-0002-0833-8191

Meryem Sena Akkuş 0000-0003-2550-550X

Publication Date June 30, 2021
Published in Issue Year 2021 Volume: 9 Issue: 1

Cite

APA Albaba, M., & Akkuş, M. S. (2021). Technologies based on energy savings for OLED devices. MANAS Journal of Engineering, 9(1), 55-65. https://doi.org/10.51354/mjen.872956
AMA Albaba M, Akkuş MS. Technologies based on energy savings for OLED devices. MJEN. June 2021;9(1):55-65. doi:10.51354/mjen.872956
Chicago Albaba, Mohammed, and Meryem Sena Akkuş. “Technologies Based on Energy Savings for OLED Devices”. MANAS Journal of Engineering 9, no. 1 (June 2021): 55-65. https://doi.org/10.51354/mjen.872956.
EndNote Albaba M, Akkuş MS (June 1, 2021) Technologies based on energy savings for OLED devices. MANAS Journal of Engineering 9 1 55–65.
IEEE M. Albaba and M. S. Akkuş, “Technologies based on energy savings for OLED devices”, MJEN, vol. 9, no. 1, pp. 55–65, 2021, doi: 10.51354/mjen.872956.
ISNAD Albaba, Mohammed - Akkuş, Meryem Sena. “Technologies Based on Energy Savings for OLED Devices”. MANAS Journal of Engineering 9/1 (June 2021), 55-65. https://doi.org/10.51354/mjen.872956.
JAMA Albaba M, Akkuş MS. Technologies based on energy savings for OLED devices. MJEN. 2021;9:55–65.
MLA Albaba, Mohammed and Meryem Sena Akkuş. “Technologies Based on Energy Savings for OLED Devices”. MANAS Journal of Engineering, vol. 9, no. 1, 2021, pp. 55-65, doi:10.51354/mjen.872956.
Vancouver Albaba M, Akkuş MS. Technologies based on energy savings for OLED devices. MJEN. 2021;9(1):55-6.

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