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

被引：0

作者：

Liu Jizhong ^{[1
,3
]}

Ma Ruyuan ^{[2
]}

Mo Yuanbin ^{[1
]}

Jin Mingliang ^{[3
]}

机构：

[1] Guangxi Univ Nationalities, Coll Mat & Comp Sci, Nanning 530006, Peoples R China

[2] Zhejiang Univ, Coll Mech Engn, Hangzhou 310000, Zhejiang, Peoples R China

[3] Nanchang Univ, Inst Robot, Nanchang 330031, Jiangxi, Peoples R China

来源：

ADVANCES IN MECHATRONICS AND CONTROL ENGINEERING II, PTS 1-3 | 2013年 / 433-435卷

关键词：

Robotic embedded vision; Compressed sensing; Measurement matrix;

D O I：

10.4028/www.scientific.net/AMM.433-435.257

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：257 / +

页数：2

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