Application of Gradient Projection for Sparse Reconstruction to Compressed Sensing for Image Reconstruction of Electrical Capacitance Tomography
Journal of Electrical and Electronic Engineering
Volume 6, Issue 2, April 2018, Pages: 46-52
Received: Jun. 19, 2018; Published: Jun. 20, 2018
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Authors
Lifeng Zhang, Department of Automation, North China Electric Power University, Baoding, China
Yajie Song, Department of Automation, North China Electric Power University, Baoding, China
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Abstract
The compressed sensing algorithm based on gradient projection for spare reconstruction (CS-GPSR) is applied to electrical capacitance tomography (ECT) image reconstruction in this paper. First, using the orthogonal basis of FFT transformation, the grey signals of original images can be sparse. Secondly, the observation matrix of ECT system was designed by rearranging the exciting-measuring order, and the capacitance measurements and corresponding sensitivity matrix can be obtained. Finally, the reconstructed images can be obtained using CS-GPSR algorithm. Simulation experiments were carried out and the results showed that the reconstructed images with higher quality can be obtained using the presented CS-GPSR algorithm, compared with conventional linear back projection (LBP) and Landweber iterative algorithms.
Keywords
Electrical Capacitance Tomography, Image Reconstruction, Compressed Sensing, Gradient Projection for Sparse Reconstruction
To cite this article
Lifeng Zhang, Yajie Song, Application of Gradient Projection for Sparse Reconstruction to Compressed Sensing for Image Reconstruction of Electrical Capacitance Tomography, Journal of Electrical and Electronic Engineering. Vol. 6, No. 2, 2018, pp. 46-52. doi: 10.11648/j.jeee.20180602.12
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