کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4970482 | 1450125 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
uAVS2-Fast encoder for the 2nd generation IEEE 1857 video coding standard
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The recently issued second generation IEEE 1857 video coding standard (AVS2) provides a doubling in coding efficiency relative to previous standards such as H.264/AVC and AVS1. The coding performance improvement is mainly due to the adoption of advanced coding tools. However, these coding tools also cause a dramatic increase in computational complexity. A fast encoder design for AVS2 is strongly demanded to promote it being widely used in video compression practice. In this paper, we propose a fast encoder design for AVS2. In our design, we propose a new quantization step (QStep) dependent fast CU depth decision algorithm for inter frames, and a combination strategy to integrate fast algorithms in different coding Presets to get a good trade-off between coding speed and coding efficiency. In addition, instruction optimization, parallel coding and some coding flow optimizations are also used in our design. According to the proposed design, we developed the first fast AVS2 encoder, and named it as uAVS2. Experimental results show that uAVS2 is 56.58 times faster than the AVS2 reference software, and 19.32 times faster than the HEVC reference software, with negligible performance loss. uAVS2 is 2.7-6.6 times faster than the well-known fast HEVC encoder x265 under similar coding performance configurations. Under similar coding speed, the coding performance of uAVS2 is superior to x265 by 10-30% in BD-rate. uAVS2 with the highest speed Preset can encode 1080Â P video in real-time on PC platform.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 53, April 2017, Pages 13-23
Journal: Signal Processing: Image Communication - Volume 53, April 2017, Pages 13-23
نویسندگان
Zhenyu Wang, Ronggang Wang, Kui Fan, Huifang Sun, Wen Gao,