Application of Gradient Projection for Sparse Reconstruction to Compressed Sensing for Image Reconstruction of Electrical Capacitance Tomography

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.