Algorithm and architecture of disparity estimation with mini-census adaptive support weight

Nelson Yen Chung Chang, Tsung Hsien Tsai, Bo Hsiung Hsu, Yi Chun Chen, Tian-Sheuan Chang

Research output: Contribution to journalArticlepeer-review

107 Scopus citations


High-performance real-time stereo vision system is crucial to various stereo vision applications, such as robotics, autonomous vehicles, multiview video coding, freeview TV, and 3-D video conferencing. In this paper, we proposed a high-performance hardware-friendly disparity estimation algorithm called mini-census adaptive support weight (MCADSW) and also proposed its corresponding real-time very large scale integration (VLSI) architecture. To make the proposed MCADSW algorithm hardware-friendly, we proposed simplification techniques such as using mini-census, removing proximity weight, using YUV color representation, using Manhattan color distance, and using scaled-and-truncate weight approximation. After applied these simplifications, the MCADSW algorithm was not only hardware-friendly, but was also 1.63 times faster. In the corresponding real-time VLSI architecture, we proposed partial column reuse and access reduction with expanded window to significantly reduce the bandwidth requirement. The proposed architecture was implemented using United Microelectronics Corporation (UMC) 90 nm complementary metal-oxide-semiconductor technology and can achieve a disparity estimation frame rate of 42 frames/s for common intermediate format size images when clocked at 95 MHz. The synthesized gate-count and memory size is 563 k and 21.3 kB, respectively.

Original languageEnglish
Article number5431623
Pages (from-to)792-805
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number6
StatePublished - 1 Jun 2010


  • Application-specific integrated circuits (ASIC)
  • Computer vision
  • Digital circuits
  • Digital integrated circuits
  • Very large scale integration (VLSI)

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