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Proceedings Paper

Hardware architecture design of a fast global motion estimation method
Author(s): Chaobing Liang; Hongshi Sang; Xubang Shen
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Paper Abstract

VLSI implementation of gradient-based global motion estimation (GME) faces two main challenges: irregular data access and high off-chip memory bandwidth requirement. We previously proposed a fast GME method that reduces computational complexity by choosing certain number of small patches containing corners and using them in a gradient-based framework. A hardware architecture is designed to implement this method and further reduce off-chip memory bandwidth requirement. On-chip memories are used to store coordinates of the corners and template patches, while the Gaussian pyramids of both the template and reference frame are stored in off-chip SDRAMs. By performing geometric transform only on the coordinates of the center pixel of a 3-by-3 patch in the template image, a 5-by-5 area containing the warped 3-by-3 patch in the reference image is extracted from the SDRAMs by burst read. Patched-based and burst mode data access helps to keep the off-chip memory bandwidth requirement at the minimum. Although patch size varies at different pyramid level, all patches are processed in term of 3x3 patches, so the utilization of the patch-processing circuit reaches 100%. FPGA implementation results show that the design utilizes 24,080 bits on-chip memory and for a sequence with resolution of 352x288 and frequency of 60Hz, the off-chip bandwidth requirement is only 3.96Mbyte/s, compared with 243.84Mbyte/s of the original gradient-based GME method. This design can be used in applications like video codec, video stabilization, and super-resolution, where real-time GME is a necessity and minimum memory bandwidth requirement is appreciated.

Paper Details

Date Published: 17 December 2015
PDF: 8 pages
Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 98110S (17 December 2015); doi: 10.1117/12.2205720
Show Author Affiliations
Chaobing Liang, Huazhong Univ. of Science and Technology (China)
Hongshi Sang, Huazhong Univ. of Science and Technology (China)
Xubang Shen, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9811:
MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis
Jinxue Wang; Zhiguo Cao; Jayaram K. Udupa; Henri Maître, Editor(s)

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