A Simple Deterministic 0-1 Measurement Matrix for Robotic Embedded Vision Compressed Sensing

Abstract:

Embedded environmental vision is a key issue for robotics. However, the image data is large, which usually will seriously affect the system processing speed and performance. Aiming at the feasibility and the real-time performance of robotic embedded vision system, by combining the up-to-date compressed sensing technology, a novel wavelet sparsity based simple deterministic 0-1 measurement matrix (0-1SDMM) is designed. The simulation results in matlab environment show that the 0-1SDMM has better performance than traditional Gaussian matrix in reconstruction result and reconstruction time. It provides an important reference for the future robotic embedded vision system.

• Periodical: Applied Mechanics and Materials (Volumes 433-435)
• Pages: 257-260
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.433-435.257
• Online since: October 2013
• Authors: Ji Zhong Liu, Ru Yuan Ma, Yuan Bin Mo, Ming Liang Jin
• Keywords: Compressed Sensing, Measurement Matrix, Robotic Embedded Vision

References

[1] Kai Zhang, Guohui Tian, Fengyu Zhou and Baoye Song: Image acquisition and transmission system for a hospital inspection robot. Journal of Shandong University ( Engineering Science) Vol. 42 No. 1 (2012), pp.51-58.

[2] Bahoura Mohammed and Ezzaidi Hassan: FPGA - implementation of discrete wavelet transform with application to signal denoising. Circuits, Systems, and Signal Processing Vol. 31 No. 3 (2012), pp.987-1015.

DOI: 10.1007/s00034-011-9355-0

[3] Ruizhen Zhao, Zhou Qin and Jinhui Tang: The method for constructing block sparse measurement matrix based on orthogonal vectors. PCM (2012), pp.872-879.

DOI: 10.1007/978-3-642-34778-8_82