NDLI: An adaptive total variation regularization method for electrical resistance tomography

Content Provider	IEEE Xplore Digital Library
Author	Yanbin Xu Xizi Song Feng Dong Huaxiang Wang
Copyright Year	2013
Description	Author affiliation: Tianjin Key Lab. of Process Meas. & Control, Tianjin Univ., Tianjin, China (Yanbin Xu; Xizi Song; Feng Dong; Huaxiang Wang)
Abstract	Total variation (TV) regularization method is widely used to solve the inverse problem of Electrical resistance tomography (ERT), which is ill-posed. However, TV regularization often suffers the staircases effect. To reduce those staircases effect, a modified TV regularization, called adaptive total variation (ATV) regularization, is proposed in this paper, which automatically adjusts the regularization term by distinguishing between edges and ramps according to the image gradients. With adaptive regularization term, at block edges it behaves more like the TV functional $(∫_{Ω}\|∇u\|dΩ)$ to perverse the edges and in ramp regions it behaves more like the $H^{1}$ functional $(∫_{Ω}\|∇u\|^{2}dΩ)$ to avoid the staircase effect. Simulation and experimental results of ATV regularization and TV regularization are compared, which show that ATV regularization can avoid the staircase effect and endure a relatively high level of noise in the measured voltages.
Sponsorship	IEEE Instrum. Meas. Soc.
Starting Page	127
Ending Page	131
File Size	1550836
Page Count	5
File Format	PDF
e-ISBN	9781467357913
DOI	10.1109/IST.2013.6729676
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	TV Image reconstruction Voltage measurement Image edge detection Tomography Noise Conductivity image reconstruction electrical resistance tomography total variation regularization adaptive total variation
Content Type	Text
Resource Type	Article

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