Kalalı, Ercan and Adıbelli, Yusuf and Hamzaoğlu, İlker (2018) A low energy intra prediction hardware for high efficiency video coding. Journal of Real-Time Image Processing, 15 (2). pp. 221-234. ISSN 1861-8200 (Print) 1861-8219 (Online)
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Official URL: http://dx.doi.org/10.1007/s11554-014-0471-5
Abstract
Intra prediction algorithm in the recently developed high efficiency video coding (HEVC) standard has very high computational complexity. Therefore, in this paper, we propose pixel equality and pixel similarity based techniques for reducing amount of computations performed by HEVC intra prediction algorithm and, therefore, reducing energy consumption of HEVC intra prediction hardware. The proposed techniques significantly reduce the amount of computations performed by 4 × 4 and 8 × 8 luminance angular prediction modes with a small comparison overhead. Pixel equality based technique does not affect the PSNR and bit rate. Pixel similarity based technique increases the PSNR slightly for some video frames and it decreases the PSNR slightly for some video frames. We also designed and implemented a low energy HEVC intra prediction hardware for 4 × 4 and 8 × 8 angular prediction modes including the proposed techniques using Verilog HDL. The proposed techniques significantly reduce the energy consumption of this HEVC intra prediction hardware.
Item Type: | Article |
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Uncontrolled Keywords: | HEVC - Intra prediction - Low energy - Hardware implementation - FPGA |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-4661 Electrical engineering. Electronics Nuclear engineering T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Electronics Faculty of Engineering and Natural Sciences |
Depositing User: | İlker Hamzaoğlu |
Date Deposited: | 12 Dec 2014 10:15 |
Last Modified: | 30 May 2023 12:40 |
URI: | https://research.sabanciuniv.edu/id/eprint/25982 |