The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Green Video Compression for Portable and Low-Power Applications
Abstract
This chapter presents recent advances in the implementation of video compression that allow for energy efficiency and management. Algorithmic complexity reduction and complexity management are key to the implementation of video compression in a green computing environment. The authors concentrate on low-power applications (such as smartphones or autonomous cameras), in which the ability to manage algorithmic complexity (and thus energy consumption) to match battery conditions and the priority of other tasks is one of the key enablers for reduced energy consumption. First, a study of the state-of-the-art video coding standard H.264/AVC and an analysis of its encoder complexity will be presented. Secondly, low complexity H.264/AVC encoder implementations will be explored in two categories as: Low Complexity Motion Estimation Algorithms and Low Complexity Mode Decision Algorithms. Later, a discussion of Complexity Scalable Encoding Algorithms that can adaptively adjust their computational complexities will follow. During the discussions, the authors will also introduce a novel framework for managing the complexity of an H.264/AVC encoder in a processor or power constrained environment as well as a complexity reduction tool. The chapter will conclude with a discussion about the future of sustainable green computing in video compression, followed by summary and concluding remarks.
Related Content
Mukul Bhatnagar, Nitin Pathak.
© 2024.
16 pages.
|
Mitushi Singh, Mukul Bhatnagar.
© 2024.
32 pages.
|
Vikas Sharma, Sanjay Taneja, Kshitiz Jangir, Kirti Khanna.
© 2024.
15 pages.
|
Preet Kanwal.
© 2024.
17 pages.
|
Kapil Sharma, Yogesh Kumar, Rajiv Khosla, Sanjay Taneja.
© 2024.
16 pages.
|
Sanjeev Kumar, Mohammad Badruddoza Talukder, Firoj Kabir, Fahmida Kaiser.
© 2024.
15 pages.
|
K. K. Kishore Mishra, Swati Priya, Syed Sajid Hussain, Swati Gupta.
© 2024.
17 pages.
|
|
|