Efficient Parameter Estimation Algorithm for Super-resolution Image
The valid method of regularized parameter estimation is to compute the maximum curvature of L-curve.However,the computation is quite costly for the estimation of the unknow n parameter in a super-resolution image reconstruction.The paper proposes an efficient approximate method based on the truncate Arnoldi process.The method can factorize the system matrix in the super-resolution reconstruction into a Hessenberg matrix by the partial Arnoldi process.The linear equations in the super-resolution reconstruction are translated into simple ones associated w ith Hessenberg matrix through the Galerkin equations.Then the equations can quickly be solved by the Given rotation translations.The formula of L-curve curvature is presented.The computational complexity of the L-curvature can be reduced through partial factorization of Arnoldi process.The theory analytics and experiments demonstrate that the method can be valid.