頭戴式顯示器是一種熱門的消費性數位產品，能藉由輸入立體影像來模擬人
類視覺系統與提供虛擬實境。而大部分的頭戴式顯示器因主動矩陣有機發光二極
體的優越的顯示特性將其作為主要顯示面板。我們提出一種基於深度資訊的動態
亮度調整演算法來降低在頭戴式顯示器中主動矩陣有機發光二極體的顯示功率。
此演算法考慮人類視覺系統對於影像不同區域分別有不同的關注度，並結合關注
度資訊與影像亮度，推導出亮度調整係數。實驗上使用兩個立體影像數據庫，並
在具有主動矩陣有機發光二極體的頭戴式顯示器上進行測試。實驗結果顯示，此
演算法能節省最多 44.26%的顯示功率，並在影像品質方面達到平均顯著度指標
(visual saliency index, VSI) 0.962，以及相比於其他省電演算法，可以達到 5.35 倍
的影像處理速度提升。

Head-mounted display (HMD) is one of the popular consumer digital products that
exploits the stereoscopic image to form the virtual reality (VR) experience based on the human visual system (HVS). Most of HMDs take the active-matrix organic light
emitting diode (AMOLED) as the primary display panel because of its displaying
superiorities. This thesis proposes a dynamic lightness adjustment algorithm to reduce the power consumption of AMOLED in HMD. The HVS has different degrees of
attention for different regions of the image. By incorporating the depth information, which indicates how a pixel attractive to HVS, and the lightness of stereoscopic image, the proposed method can determine a lightness adjustment ratio. According to the experiments of two stereoscopic image datasets on AMOLED in HMD, the proposed
method can achieve up to 44.26% of power-saving rate. In term of image quality, the
proposed method provides mean visual saliency index of 0.962 and the time cost is 5.35 times faster than the existing power saving scheme.

[1] David E. Mentley, “State of Flat-Panel Display Technology and Future Trends,” Proceedings of the IEEE, vol. 90, no. 4, pp. 453- 459, April 2002.

[2] David Hsieh, “Flat Panel Display Market & Technology Outlook,” IHS Markit Technology, 2018, [Online]. Available: http://xqdoc.imedao.com/16184d36f5150de13fd3f231.pdf.

[3] W. den Boer, Active Matrix Liquid Crystal Displays: Fundamentals and Applications, Newnes, Burlington, 2005.

[4] S.R.P. Silva, J.D. Carey, G.Y. Chen, D.C. Cox, R.D. Forrest, C.H.P. Poa, R.C. Smith, Y.F. Tang, and J.M. Shannon, “Nanoengineering of Materials for Field Emission Display Technologies,” Proc. IEE Circuits, Devices and Syst., vol. 151, no. 5, pp. 489–496, Oct. 2004.

[5] M. Dong and L. Zhong, “Power Modeling and Optimization for OLED Displays,” IEEE Trans. Mobile Comput., vol. 11, no. 9, pp. 1587-1599, Sept. 2012.

[6] M. Dong and L. Zhong, “Chameleon: A Color-Adaptive Web Browser for Mobile OLED Displays,” In Proceedings of the 9th international conference on Mobile systems, applications, and services, MobiSys ’11, pages 85–98, 2011.

[7] N. Chang, I. Choi, and H. Shim, “DLS: Dynamic Backlight Luminance Scaling of Liquid Crystal Display,” IEEE Trans. Very Large Scale Integration (VLSI) Systems, vol. 12, pp. 837-846, 2004.

[8] M. Dong and L. Zhong, “Self-Constructive High-Rate System Energy Modeling for Battery-Powered Mobile Systems,” In Proceedings of the 9th international conference on Mobile systems, applications, and services, MobiSys ’11, pages 335–348, 2011.

[9] M. Dong, Y.-S. Choi, and L. Zhong, “Power-Saving Color Transformation of Mobile Graphical User Interfaces on OLED-Based Displays,” Proc. ACM/IEEE Int. Symp. Low Power Electron. Design, New York, 2009, pp. 339-342.

[10] C.-K. Kangand, C.-H. Linand and P.-C. Hsiu, “A Win-Win Camera: Quality-Enhanced Power-Saving Images on Mobile OLED Displays,” in 2015 IEEE Int. Symp. Low Power Electron. Design, Rome, 2015, pp.267–272.

[11] Mon-Williams, M., Wann, J. P., & Ruston, S., “Binocular Vision in A Virtual World: Visual Deficits Following the Wearing of A Head-Mounted Display,” Ophthalmology and Physiological Optics, 13, 387–391, 1993.

[12] D. Shin, Y. Kim, N. Chang, and M. Pedram, “Dynamic Voltage Scaling of OLED Displays,” in Proc. of IEEE/ACM DAC, 2011, pp. 53–58.

[13] 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 Proc. of IEEE/ACM DAC, 2012, pp. 1000–1005.

[14] C. Lee, C. Lee, C.-S. Kim, “Power-Constrained Contrast Enhancement for OLED Displays Based on Histogram Equalization,” Proc. IEEE ICIP, pp. 1689-1692, 2010-Sep.

[15] L.-M. Jan, F.-C. Cheng, C.-H. Chang, S.-J. Ruan, C.-A. Shen, “A Power-Saving Histogram Adjustment Algorithm for OLED-Oriented Contrast Enhancement,” IEEE/OSA J. Display Technol., vol. 12, no. 4, pp. 368-375, Oct. 2015.

[16] Y.-T. Peng, F.-C. Cheng, L.-M. Jan and S.-J. Ruan, “Histogram Shrinking for Power-Saving Contrast Enhancement,” in Proc. IEEE Int. Conf. Image Process., Melbourne, pp. 891-894, 2013.

[17] T.-C. Chang, S.S.-D. Xu and S.-F. Su, “SSIM-Based Quality on Demand Energy Saving for OLED Displays,” IEEE trans. Syst. ManCybern. A., Syst. Humans, vol. 46, no. 5, pp. 623-635, May. 2016.

[18] P. Chondro, and S.-J. Ruan, “Perceptually Hue-Oriented Power-Saving Scheme with Overexposure Corrector for AMOLED Displays,” J. Display Technology., vol. 12, no. 8, pp. 791-800, Mar. 2016.

[19] C.-H. Lin, C.-K. Kang, and P.-C. Hsiu, “CURA: A Framework for Quality-Retaining Power Saving on Mobile OLED Displays,” ACM Transactions on Embedded Computing Systems, vol. 15, no. 4, article 76, 2016.

[20] Y.-O. Nam, D.-Y. Choi, 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.

[21] M. Park, M. Song, “Saving Power in Video Playback on OLED Displays by Acceptable Changes to Perceived Brightness,” J. Display Technol., vol. 12, no. 5, pp. 483-490, May 2016.

[22] 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. PP, no. 99, pp. 1-1, Jul. 2017.

[23] B. Geffroy, P.L. Roy, and C. Prat, “Organic Light-Emitting Diode (OLED) Technology: Materials, Devices and Display Technologies,” Polym. Int., vol. 55, no. 6, pp. 572-582, Jun. 2006.

[24] S. Reichelt, R. Hussler, G. Ftterer, and N. Leister, “Depth Cues in Human Visual Perception and Their Realization in 3D Displays,” in Proc. Three-Dimensional Imaging, Visualization, and Display 2010 and Display Technologies and Applications for Defense, Security, and Avionics IV, Orlando, FL, Apr. 2010.

[25] Y.-S. Chen, Y.-P. Huang, and C.-S. Fuh, “Fast Block Matching Algorithm Based on the Winner-Update Strategy,” IEEE Trans. Image Processing, vol. 10, no. 8, pp. 1212–1222, 2001.

[26] M.Z. Brown, D. Burschka, G.D. Hager, “Advances in Computational Stereo,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 993-1008, Aug. 2003.

[27] Bradski, G. The OpenCV Library. Dr. Dobb's Journal of Software Tools, 2000.

[28] T. Tan and R. Balan. “Adaptive Display Power Management for OLED Displays,” In Proceedings of the ACM Workshop on Mobile Gaming, pages 25–30, Aug. 2012.

[29] B. Anand, K. Thirugnanam, J. Sebastian, and P. Kannan. “Adaptive Display Power Management for Mobile Games,”. In Proceedings of the ACM Conference on Mobile Systems, Applications, and Services, pages 57–70, June 2011.

[30] J. Schwiegerling, Field Guide to Visual and Ophthalmic Optics, WA, Bellingham: SPIE, 2004.

[31] B.X. Chen, R. Sahdev and J.K. Tsotsos, “Person Following Robot using Selected Online Ada-Boosting with Stereo Camera,” in 14th Conference on Computer and Robot Vision (CRV), pp 48-55, IEEE, 2017.

[32] B.X. Chen, R. Sahdev and J.K. Tsotsos, “Integrating Stereo Vision with A CNN Tracker for A Person-Following Robot,” in International Conference on Computer Vision Systems (ICVS), pp. 300-313, Springer, 2017.

[33] D. J. Butler, J. Wulff, G. B. Stanley, M. J. Black, “A Naturalistic Open Source Movie for Optical Flow Evaluation,” Proceedings of the European Conference on Computer Vision (ECCV), pp. 611-625, Oct. 2012.

[34] L. Zhang, Y. Shen, and H. Li, “VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment,” IEEE Trans. on Image Processing, vol. 23, no. 10, pp. 4270–4281, Oct 2014.

[35] L. Zhang, Y. Shen, and H. Li, “VSI: A Visual Saliency based IQA Index,” Sse.tongji.edu.cn, 2014. [Online]. Available: http://sse.tongji.edu.cn/linzhang/IQA/VSI/VSI/htm.

[36] Zhou, W., A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. “Image Quality Assessment: From Error Visibility to Structural Similarity,” IEEE Transactions on Image Processing. Vol. 13, Issue 4, April 2004, pp. 600–612.

[37] L. Zhang, D. Zhang, X. Mou and D. Zhang, “FSIM: A Feature Similarity Index for Image Quality Assessment,” IEEE Trans. Image Process., vol. 20, no. 8, pp. 2378-2386, Aug. 2011.

[38] L. Zhang, D. Zhang, X. Mou and D. Zhang, “FSIM: A Feature Similarity Index for Image Quality Assessment,” Sse.tongji.edu.cn, 2013. [Online]. Available: http://sse.tongji.edu.cn/linzhang/IQA/FSIM/FSIM.htm