@inproceedings{a670e340c38945b6a8418434e5a9df33,
title = "A new fast algorithm for sample adaptive offset",
abstract = "Sample Adaptive Offset is a new adopted technology by HEVC in recent years, which improves the visual quality of reconstructed videos significantly. However, there are two problems in current SAO technology. The first is that the statistic phase needs to traverse each pixel to collect relevant information. The other problem is that the complexity of SAO is too high for SAO mode decision stage, which needs to be performed on each CTU. To solve these problems, we proposed a fast SAO algorithm in HEVC encoder. We explore the correlation of SAO type among neighboring CTUs, and then utilize this spatial information to reduce the complexity of SAO. Experimental results demonstrate that our proposed method can achieve about 62\%, 80\% and 75\% SAO encoding time saving on average in AI, RA, and LDB test condition compared with HM16.0 respectively. At the same time, the proposed method just causes negligible compression performance loss.",
keywords = "HEVC, Merge, SAO, Statistic",
author = "Chentian Sun and Yang Wang and Xiaopeng Fan and Debin Zhao",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 18th Pacific-Rim Conference on Multimedia, PCM 2017 ; Conference date: 28-09-2017 Through 29-09-2017",
year = "2018",
doi = "10.1007/978-3-319-77383-4\_38",
language = "英语",
isbn = "9783319773827",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "388--396",
editor = "Bing Zeng and Hongliang Li and Qingming Huang and \{El Saddik\}, Abdulmotaleb and Shuqiang Jiang and Xiaopeng Fan",
booktitle = "Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers",
address = "德国",
}