Computationally efficient image reconstruction algorithm for electrical capacitance tomography

Abstract

The electrical capacitance tomography (ECT) is a visualization measurement method and can reconstruct the spatial permittivity distribution information in a measurement domain based on given capacitance values, in which the effectiveness of the image reconstruction algorithm plays a vital role in real-world engineering applications. Unlike common imaging methods, within the framework of the Tikhonov regularization methodology and the transform-domain sparsity method, a new cost function encapsulating the wavelet-based sparsity constraint is proposed to model the ECT imaging problem. An iteration scheme that integrates the superiorities of the alternating direction method of multipliers algorithm and splits a complicated optimization problem into several simpler sub-problems is developed to seek for the optimal solution of the proposed cost function. Numerical experiments validate that the proposed imaging algorithm is practicable and effective, and can improve the reconstruction accuracy and robustness.

Iterative weighted fidelity and hybrid regularization-based algorithm for ECT

“…But they only considered the sparsity as the single prior information. Moreover, to overcome the limitation of the single prior methods, Tong et al [27] proposed a new cost function with hybrid regularization terms to reduce the artifacts, in which the sparsity and low rank properties of the imaging objects are considered. Guo et al [28] combined the L1-norm and second order total variation (STV) as the regularizers to enhance sparsity and alleviate the staircasing effect.…”

The Concept of Using LSTM to Detect Moisture in Brick Walls by Means of Electrical Impedance Tomography

“…On the other hand, ERT is utilised to recognise geological structures [14][15][16], such as aquifers, aggregates, and metal deposits [8,13,17]. With ECT, the electrical permittivity is determined [18][19][20], but with EIT and ERT, the conductivity is reconstructed [2]. Apart from electrical tomography (EIT, ECT, ERT) [15] and computed tomography (CT) [21], there are numerous other varieties, which can be classified according to the physical phenomenon used: X-rays [22], sound waves [23], magnetism [24][25][26], electromagnetic waves, and visible light [27].…”

Electrical capacitance tomography image reconstruction by improved orthogonal matching pursuit algorithm

“…At present, reconstruction methods based on the CS theory have been extended for ECT image reconstruction [13,[19][20][21][22][23][24], and the grey-value vector of the image to be reconstructed is transformed into a sparse signal usually by a sparse transform [21][22][23][24]. However, the signal sparsity before and after the sparse transform is not compared, and the fidelity of the sparse signal obtained after the sparse transform to the original signal under different sparsity degrees is not considered.…”