Abstract
Smart devices have become an integral part of people’s lives. The most common activities for users of such smart devices that are energy sources are voice calls, text messages (SMS) or email, browsing the World Wide Web, streaming audio/video, and using sensor devices such as cameras, GPS, Wifi, 4G/5G, and Bluetooth either for entertainment or for the convenience of everyday life. In addition, other power sources are the device screen, RAM, and CPU. The need for communication, entertainment, and computing makes the optimal management of the power consumption of these devices crucial and necessary. In this paper, we employ a computationally efficient linear mapping algorithm known as Concurrent Brightness & Contrast Scaling (CBCS), which transforms the initial intensity value of the pixels in the YCbCr color system. We introduce a methodology that gives the user the opportunity to select a picture and modify it using the suggested algorithm in order to make it more energy-friendly with or without the application of a histogram equalization (HE). The experimental results verify the efficacy of the presented methodology through various metrics from the field of digital image processing that contribute to the choice of the optimal values for the parameters that meet the user’s preferences (low or high-contrast images) and green power. For both low-contrast and low-power images, the histogram equalization should be omitted, and the appropriate a should be much lower than one. To create high-contrast and low-power images, the application of HE is essential. Finally, quantitative and qualitative evaluations have shown that the proposed approach can achieve remarkable performance.
Highlights
The penetration of smart devices into their users’ daily lives is prevalent
We found that the appropriate values of the parameters a, b that make the power reduction rate (PRR) positive maximize the SSI M and Peak Signal-to-Noise Ratio (PSNR), and minimize the Mean Squared Error (MSE) are in the range 0.5 ≤ a ≤ 1, 10 ≤ b ≤ 200, respectively
Power Constrained Contrast Enhancement (PCCE) performs an unconstrained optimization of power and contrast controlled by a single parameter, while the LowOverhead Adaptive Power Saving and Contrast Enhancement (LAPSE) [38] minimized power under a mean SSI M (MSSI M) constraint
Summary
The penetration of smart devices into their users’ daily lives (irrespective of age) is prevalent. Due to the limited size and capacity of the batteries, the efficient and effective use of energy is critical to the functionality and usability of the mobile device. These devices include an operating system with advanced computing ability and connectivity. The power consumption of a mobile device depends on many factors [2]. These include the technical characteristics of the device, environmental conditions, and user’s behavior separately. The main sources of energy consumption associated with the user’s activities of such smart devices include video and voice calls, sending and receiving messages, browsing the World Wide Web, audio and video streaming
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
