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Gauss quadrature rule based on parameter estimation

In this paper, we consider the estimation of the unknown parameter for the problem of reconstructing a high resolution image from multiple under-sampled, shifted, degraded frames. L-curve criterion is used to estimate regularization parameters. However, the computational of the L-curve is quiet costly for large-size problems. The paper proposes an efficient approximate technique based on Gauss quadrature rule. The technique translates some matrix computation into Gauss quadrature with singular decomposition. It can reduce the computational complexity of the L-curve.