26 research outputs found

    Image Dependent Energy-Constrained Local Backlight Dimming

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    TV Energy Consumption Trends and Energy-Efficiency Improvement Options

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    ์œ ๊ธฐ๋ฐœ๊ด‘ ๋‹ค์ด์˜ค๋“œ ํ‘œ์‹œ์žฅ์น˜๋ฅผ ์žฅ์ฐฉํ•œ ์ด๋™ํ˜• ์‹œ์Šคํ…œ์˜ ์ „๋ ฅ ๊ณต๊ธ‰ ์ตœ์ ํ™”

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2012. 8. ์žฅ๋ž˜ํ˜.์˜ค๋Š˜๋‚  ์Šค๋งˆํŠธํฐ, ํƒœ๋ธ”๋ฆฟ PC ์™€ ๊ฐ™์€ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ๋Š” ๊ณ ์„ฑ๋Šฅ์˜ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜ (CPU), ๋Œ€์šฉ๋Ÿ‰ ๋ฉ”๋ชจ๋ฆฌ, ๋Œ€ํ˜• ํ™”๋ฉด, ๊ณ ์†์˜ ๋ฌด์„  ์ธํ„ฐํŽ˜์ด์Šค ๋“ฑ์„ ํƒ‘์žฌํ•จ์—๋”ฐ๋ผ ์ „ ๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ๊ธ‰์†ํžˆ ์ฆ๊ฐ€ํ•˜์—ฌ ๊ทธ ์ „๋ ฅ ์†Œ๋ชจ๋Š” ์ด๋ฏธ ์†Œํ˜•์˜ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์ˆ˜์ค€์— ์ด๋ฅด๊ณ  ์žˆ๋‹ค. ์„ฑ๋Šฅ๊ณผ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์˜ ์ธก๋ฉด์—์„œ ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์™€ ๋žฉํƒ‘ ์ปดํ“จํ„ฐ ์‚ฌ ์ด์˜ ๊ตฌ๋ถ„์ด ์ ์ฐจ ์‚ฌ๋ผ์ง€๊ณ  ์žˆ์Œ์—๋„ ๋ฐฐํ„ฐ๋ฆฌ ๋ฐ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ๋Š” ๊ธฐ์กด์˜ ์„ค๊ณ„ ์›์น™๋“ค๋งŒ์„ ๋”ฐ๋ผ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ์‚ผ์„ฑ์ „์ž์˜ ๊ฐค๋Ÿญ์‹œ ํƒญ ๋ฐ Apple ์‚ฌ์˜ iPad ๋“ฑ ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC์˜ ๊ฒฝ์šฐ 1-cell ์ง๋ ฌ ๋ฆฌํŠฌ ์ด์˜จ ์ „์ง€๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋ฐ˜ ๋ฉด, ๋žฉํƒ‘ ์ปดํ“จํ„ฐ์˜ ๊ฒฝ์šฐ๋Š” ์ œ์กฐ์‚ฌ์— ๋”ฐ๋ผ 3-cell ์—์„œ 5-cell ์ง๋ ฌ ๋“ฑ์œผ๋กœ ์„ค๊ณ„๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๋ฐฐํ„ฐ๋ฆฌ ์ถœ๋ ฅ ์ „์••์„ ๋‹ค๋ฅด๊ฒŒ ํ•จ์œผ๋กœ์จ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์— ์˜ํ–ฅ์„ ์ค€๋‹ค. ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ์˜ ์ˆ˜๋ช…์€ ์ž…์ถœ๋ ฅ ์ „์••/์ „๋ฅ˜๋ฅผ ๋น„๋กฏํ•œ ๋™์ž‘ ํ™˜๊ฒฝ์˜ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ํœด๋Œ€์šฉ ์ „์ž๊ธฐ๊ธฐ์— ์‚ฌ์šฉ๋˜๋Š” ๊ฐ์ข… ์ „์ž๋ถ€ํ’ˆ์€ ์ „๋ ฅ ์†Œ๋ชจ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๊ธฐ๋Šฅ๋“ค์„ ๊ตฌํ˜„ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ ์ˆ˜ ์กฐ์ ˆ ๊ธฐ๋ฒ• ๋“ฑ ๊ณต๊ธ‰์ „์••์˜ ๋ณ€ํ™”๋ฅผ ์ˆ˜๋ฐ˜ํ•˜๋Š” ๊ธฐ๋ฒ• ์—ญ์‹œ ๋‹ค์–‘ํ•˜๊ฒŒ ์ ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๊ฐ ์žฅ์น˜์˜ ๊ณต๊ธ‰ ์ „์•• ๋ฐ ์ „๋ฅ˜์˜ ๋ณ€ํ™”๋กœ ์ธํ•œ ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ์˜ ํšจ์œจ์˜ ๋ณ€ํ™” ๋ฅผ ์ดˆ๋ž˜ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜, ๋””์Šคํ”Œ๋ ˆ์ด ๋“ฑ ์ฃผ์š” ์ „๋ ฅ ์†Œ๋น„ ์žฅ์น˜์˜ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•  ๋•Œ์—๋Š” ๊ฐœ๋ณ„ ์žฅ์น˜์˜ ์ „๋ ฅ ์†Œ๋น„๋ฅผ ์ค„์ด๋Š” ๊ฒƒ๊ณผ ๋™์‹œ์— ๊ฐœ๋ณ„ ์žฅ ์น˜์˜ ๋™์ž‘ ํ–‰ํƒœ์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋ฐฐํ„ฐ๋ฆฌ, ์ „๋ ฅ ๋ณ€ํ™˜ํšŒ๋กœ์˜ ์„ค๊ณ„๊ฐ€ ํ•จ๊ป˜์ด๋ฃจ์–ด์ ธ์•ผ ํ•œ๋‹ค. ์„ ํ–‰ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ฐฐํ„ฐ๋ฆฌ์˜ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์˜ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [1]. ์ค‘์•™์ฒ˜๋ฆฌ์žฅ์น˜์˜ ๋™์  ์ „์••/์ฃผํŒŒ์ˆ˜ ์ œ์–ด ๊ธฐ๋ฒ•์— ์ด์–ด ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ(OLED) ๊ธฐ๋ฐ˜ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค [2]. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด๋Š” ์ „๋ ฅ ์†Œ๋ชจ ๋ฐ ์‹œ์•ผ๊ฐ ๋“ฑ ๊ธฐ์กด ์•ก์ • ํ‘œ์‹œ์žฅ์น˜์— ๋น„ํ•ด ์—ฌ๋Ÿฌ ์šฐ์ˆ˜ํ•œ ํŠน์„ฑ์œผ๋กœ ์ธํ•ด ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋Š” ์ฐจ์„ธ๋Œ€ ๋””์Šคํ”Œ๋ ˆ์ด ์žฅ์น˜์ด๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค ์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ ์€ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ™”๋ฉด์˜ ๋Œ€ํ˜•ํ™” ๋ฐ ํ•ด์ƒ๋„์˜ ๊ณ ๋ฐ€๋„ํ™”์— ๋”ฐ๋ผ ์‹œ์Šคํ…œ ์ „๋ ฅ ์†Œ๋ชจ์—์„œ ์—ฌ์ „ํžˆ ํฐ ๋น„์ค‘์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ๋‹ค. ์œ ๊ธฐ๋ฐœ ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•(OLED DVS)๋Š” ์ƒ‰์ƒ์˜ ๋ณ€ํ™”์˜ ๊ธฐ์ดˆํ•œ ๊ธฐ์กด์˜ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ตœ ์†Œํ•œ์˜ ์ด๋ฏธ์ง€ ์™œ๊ณก๋งŒ์„ ์ˆ˜๋ฐ˜ํ•˜์—ฌ ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ์ง„, ๋™์˜์ƒ ๋“ฑ์— ์ ์šฉ๊ฐ€๋Šฅํ•œ ์ „๋ ฅ ์ ˆ๊ฐ ๊ธฐ๋ฒ•์ด๋‹ค. ํ•ด๋‹น ๊ธฐ๋ฒ•์€ ๊ณต๊ธ‰ ์ „์••์˜ ๋ณ€ํ™”์‹œํ‚ฌ ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ์‹œ์Šคํ…œ์— ์˜ฌ๋ฐ”๋ฅด๊ฒŒ ํ†ตํ•ฉ์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ „๋ ฅ ๋ณ€ํ™˜ ํšŒ๋กœ ๋ฐ ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ์ „๋ ฅ ์†Œ๋ชจ์™€ ํ•จ๊ป˜ ์ „์ฒด ์‹œ์Šค ํ…œ ํšจ์œจ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜์—ฌ ์‹œ์Šคํ…œ์„ ์ตœ์ ํ™”ํ•œ๋‹ค. ๋ฐฐํ„ฐ๋ฆฌ ๊ตฌ์„ฑ ์—ญ ์‹œ ๊ธฐ์กด์˜ ์„ค๊ณ„ ํ‘œ์ค€ ๋Œ€์‹  ์ฒด๊ณ„์ ์ธ ์‹œ์Šคํ…œ ๋ถ„์„์— ๊ธฐ๋ฐ˜ํ•œ ์ตœ์ ํ™”๊ฐ€ ์‹œ๋„๋˜์—ˆ๋‹ค. ๊ณต๊ธ‰์ „์••์ด ์กฐ์ ˆ ๊ฐ€๋Šฅํ•œ ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด ํ•˜๋“œ์›จ์–ด ๋ฐ ์ œ์–ด๊ธฐ ์‹œ์Šค ํ…œ-์˜จ-์นฉ (System-on-a-chip, SoC) ๊ฐ€ ์ œ์ž‘๋˜์—ˆ๊ณ , ๊ทธ ๋™์ž‘ ํŠน์„ฑ์ด ๋ถ„์„๋˜์—ˆ๋‹ค. ๊ธฐ์กด ์Šค๋งˆํŠธํฐ ๋ฐ ํƒœ๋ธ”๋ฆฟ PC ๊ฐœ๋ฐœ์šฉ ํ”Œ๋žซํผ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ ๋ฐ ๋™์ž‘ ํŠน์„ฑ ์—ญ์‹œ ๋ถ„์„ ๋˜์—ˆ๋‹ค. ์œ ๊ธฐ๋ฐœ๊ด‘๋‹ค์ด์˜ค๋“œ ๋””์Šคํ”Œ๋ ˆ์ด์˜ ๋™์  ๊ตฌ๋™ํšŒ๋กœ ๊ณต๊ธ‰ ์ „์•• ๊ธฐ๋ฒ•์˜ ๋™์ž‘ ํŠน์„ฑ ๋ฐ ์Šค๋งˆํŠธํฐ ํ”Œ๋žซํผ์˜ ๋™์ž‘ ํŠน์„ฑ, ๋ฐฐํ„ฐ๋ฆฌ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋ถ„์„์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์‹œ์Šค ํ…œ ์ˆ˜์ค€์—์„œ์˜ ์ „๋ ฅ ๋ณ€ํ™˜ ํšจ์œจ์ด ์ตœ์ ํ™”๋˜์—ˆ๋‹ค.Modern mobile devices such as smartphone or tablet PC are typically equipped a high-performance CPU, memory, wireless interface, and display. As a result, their power consumption is as high as a small-size laptop computer. The boundary between the mobile devices and laptop computer is becoming unclear from the perspective of the performance and power. However, their battery and related power conversion architecture are only designed according to the legacy design so far. Smartphone and tablet PCs from major vendors such as iPad from Apple or Galaxy-tab from Samsung uses 1-cell Li-ion battery. The laptop PC typically has 3-cell Li-ion battery. The output voltage of the battery affect system-level power conversion efficiency. Furthermore, traditional power conversion architecture in the mobile computing system is designed only considering the fixed condition where the system-level low-power techniques such as DVFS are becoming mandatory. Such a low-power techniques applied to the major components result in not only load demand fluctuation but also supply voltage changing. It has an effect on the battery lifetime as well as the system-level power delivery efficiency. The efficiency is affected by the operating condition including input voltage, output voltage, and output current. We should consider the operating condition of the major power consumer such as a display to enhance the system-level power delivery efficiency. Therefore, we need to design the system not only from the perspective of the power consumption but also energy storage design. The optimization of battery setup considering battery characteristics was presented in [1]. Beside the DVFS of microprocessor, a power saving technique based on the supply voltage scaling of the OLED driver circuit was recently introduced [2]. An organic light emitting diode (OLED) is a promising display device which has a lot of advantages compared with conventional LCD, but it still consumes significant amount of power consumption due to the size and resolution increasing. The OLED dynamic voltage scaling (OLED DVS) technique is the first OLED display power saving technique that induces only minimal color change to accommodate display of natural images where the existing OLED low-power techniques are based on the color change. The OLED DVS incurs supply voltage change. Therefore we need to consider the system-level power delivery efficiency and battery setup to properly integrate the DVS-enabled OLED display to the system. In this dissertation, we not only optimize the power consumption of the OLED display but also consider its effect on the whole system power efficiency. We perform the optimization of the battery setup by a systematic method instead of the legacy design rule. At first, we develop an algorithm for the OLED DVS for the still images and a histogram-based online method for the image sequence with a hardware board and a SoC. We characterize the behavior of the OLED DVS. Next, we analyze the characteristics of the smartphone and tablet-PC platforms by using the development platforms. We profile the power consumption of each components in the smartphone and power conversion efficiency of the boost converter which is used in the tablet-PC for the display devices. We optimize not only the power consuming components or the conversion system but also the energy storage system based on the battery model and system-level power delivery efficiency analysis.1 Introduction 1.1 Supply Voltage Scaling for OLED Display 1.2 Power Conversion Efficiency in MobileSystems 1.3 Research Motivation 2 Related Work 2.1 Low-Power Techniques for Display Devices 2.1.1 Light Source Control-Based Approaches 2.1.2 User Behavior-Based Approaches 2.1.3 Low-Power Techniques for Controller and Framebuffer 2.1.4 Pre-ChargingforOLED 2.1.5 ColorRemapping 2.2 Battery discharging efficiency aware low-power techniques 2.2.1 Parallel Connection 2.2.2 Constant-Current Regulator-Based Architecture 2.3 System-level power analysis techniques 3 Preliminary 38 3.1 Organic Light Emitting Diode (OLED) Display 3.1.1 OLED Cell Architecture 3.1.2 OLED Panel Architecture 3.1.3 OLED Driver Circuits 3.2 Effect of VDD scaling on driver circuits 3.2.1 VDD scaling for AM drivers 3.2.2 VDD scaling for PWM drivers 4 Supply Voltage Scaling and Image Compensation of OLED displays 4.1 Image quality and power models of OLED panels 4.2 OLED display characterization 4.3 VDD scaling and image compensation 5 OLED DVS implementation 5.1 Hardware prototype implementation 5.2 OLED DVS System-on-Chip implementation 5.3 Optimization of OLED DVS SoC 5.4 VDD transition overhead 6 Power conversion efficiency and delivery architecture in mobile Systems 6.1 Power conversion efficiency model of switching-Mode DCโ€“DC converters 6.2 Power conversion efficiency model of linear regulator power loss model 6.3 Rate Capacity Effect of Li-ion Batteries 7 Power conversion efficiency-aware battery setup optimization with DVS- enabled OLED display 7.1 System-level power efficiency model 7.2 Power conversion efficiency analysis of smartphone platform 7.3 Power conversion efficiency for OLED power supply 7.4 Li-ion battery model 7.4.1 Battery model parameter extraction 7.5 Battery setup optimization 8 Experiments 8.1 Simulation result for OLED display with AM driver 8.2 Measurement result for OLED display with PWM driver 8.3 Design space exploration of battery setup with OLED displays 9 Conclusion 10 Future WorkDocto

    Power Consumption Analysis, Measurement, Management, and Issues:A State-of-the-Art Review of Smartphone Battery and Energy Usage

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    The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed

    Smartphone Power Consumption Characterization and Dynamic Optimization Techniques for OLED Display

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    Smartphones have emerged as the most popular and frequently used platform for the consumption of multimedia. Following the rapid growth of application number and the explosion of cellular network bandwidth, high power consumption, and limited battery capacity remain as the major challenges in smartphone designs. Therefore, lots of research is made to characterize and optimize the smartphone power performance. However, the existing research approaches on smartphone power characterization generally ignore the impact from the components' varying performance in different applications, as well as users' behavior during the practical usage. Hence, the power optimization techniques in the modern smartphone are inflexible to adapt to different application scenarios and user behaviors. In this dissertation, I first proposed a new smartphone power consumption characterization and analysis approach -- ``SEER'', which was associated with both user ethological and smartphone evolutionary perspectives. The real-time power consumption is measured with a set of the most popular applications on different generations of Samsung Galaxy smartphones. And deep analysis is made to find how each smartphone component is utilized in different applications, and how the users' daily usage patterns impact on final energy consumption. The experiments show that some traditional power-hungry components, such as Wi-Fi and CPU, actually consume much less energy in practical daily usage. Meanwhile, OLED display panel is still the biggest power consumer in the whole smartphone system; even it's considered the most promising low power display technology. To further optimize the display power consumption with OLED. I further proposed a set of dynamic power optimization techniques for OLED display, balancing the real-time power performance and the user visual perception experience. In this dissertation, the optimization is full-filled at three different levels: 1) Hardware based Optimization: Based on the traditional AMOLED display pixel driver, a novel DVS-friendly OLED driver design is proposed, which can minimize the display color distortion under aggressive supply voltage scaling. Correlated fine-grained DVS schemes (DiViCi) are also proposed to utilize the DVS-friendly driver into video streaming applications. 2) Software based Optimization: Despite the hardware modification, a dynamic OLED power model is built to evaluate the OLED panel power consumption and human visual perception quality assessment. A novel video category based dynamic tone mapping (DaTuM) technique is proposed for video streaming; 3) User Interaction based Optimization: The user interaction and visual perception during the display content capture phase are also taken into consideration, a novel OLED power friendly video recording application (MORPh) was also proposed. Dedicated real-time management and reliability enhancement schemes are explored to promote the applicability of the proposed approaches . Experiments show that, with these power optimization techniques, the OLED display panel power performance on smartphone device is significantly improved with reasonable visual quality controllability

    Image Processing for Machine Vision Applications

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    L'abstract รจ presente nell'allegato / the abstract is in the attachmen
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