Fast SAO estimation algorithm and its implementation for 8K × 4K @ 120 FPS HEVC encoding

Jiayi Zhu, Dajiang Zhou, Shinji Kimura, Satoshi Goto

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


High efficiency video coding (HEVC) is the new generation video compression standard. Sample adaptive offset (SAO) is a new compression tool adopted in HEVC which reduces the distortion between original samples and reconstructed samples. SAO estimation is the process of determining SAO parameters in video encoding. It is divided into two phases: statistic collection and parameters determination. There are two difficulties for VLSI implementation of SAO estimation. The first is that there are huge amount of samples to deal with in statistic collection phase. The other is that the complexity of Rate Distortion Optimization (RDO) in parameters determination phase is very high. In this article, a fast SAO estimation algorithm and its corresponding VLSI architecture are proposed. For the first difficulty, we use bitmaps to collect statistics of all the 16 samples in one 4 × 4 block simultaneously. For the second difficulty, we simplify a series of complicated procedures in HM to balance the algorithms complexity and BD-rate performance. Experimental results show that the proposed algorithm maintains the picture quality improvement. The VLSI design based on this algorithm can be implemented using 156.32 K gates, 8,832 bits single port RAM for 8 bits depth case. It can be synthesized to 400 MHz @ 65 nm technology and is capable of 8K × 4K @ 120 fps encoding.

Original languageEnglish
Pages (from-to)2488-2497
Number of pages10
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number12
Publication statusPublished - 2014 Dec 1


  • High efficiency video coding
  • Rate Distortion Optimization (RDO) VLSI architecture
  • Sample adaptive offset

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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