Discrete cosine transform LSQR methods for multidimensional ill-posed problems

We propose new tensor Krylov subspace methods  for ill-posed linear tensor problems such as color or video image restoration. Those methods are based on the tensor-tensor discrete cosine transform that gives fast tensor-tensor product computations. In particular, we will focus on the tensor discrete cosine versions of GMRES, Golub-Kahan bidiagonalisation and LSQR methods. The presented numerical tests show that the methods are very fast and give good accuracies when solving some linear tensor ill-posed problems.

کلیدواژه های Discrete cosine transform LSQR methods for multidimensional ill-posed problems:

Discrete cosine product ، Golub-Kahan bidiagonalisation ، GMRES ، LSQR ، tensor Krylov subspaces