Abstract:Aiming at the problem of the loss of the details of the reconstructed image caused by excessive smoothness of the Tiknonov regularization in the image reconstruction of electrical capacitance tomography(ECT) system, an image reconstruction model with norm l2,p(0<p≤1), which combines the smoothness of Euclid normand the sparsity of norm lp(0<p≤1) matrix norm is presented, which is non-convex and non-Lipschitz continuous problem . The extensive experiments have showed, the l2,p-minimization, which has stronger adaptability, higher resolution and better image quality, is better than the Newton iterative method, conjugate gradient method and traditional singular value decomposition algorithm.
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