Now many image super-resolution methods suppose that the optical flows between images should be
computed accurately. But really it is very difficult to get them and the models of imaging systems are
unknown almost. Thurs perturbation errors always occur in the image super-resolution model. The
paper proposes an improved image super-resolution algorithm based on total least squares method. The
average image based on images is used as regularized penalty for posteriori probability model. The
paper presents the improved Rayleigh quotient format for energy objective function. Then a conjugate
gradient algorithm is used to minimize the modified Rayleigh quotient function. The method can
minimize two the errors from the sampled low-resolution images and in that perturbation system matrix
of high-resolution reconstruction. The test results showed that the algorithm is stable for the
perturbation system matrix.
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