Abstract
It is shown how the efficient recursive total least squares algorithm recently developed by C.E. Davila [3] for real data can be applied to image reconstruction from noisy, undersampled multiframes when the displacement of each frame relative to a reference frame is not accurately known. To do this, the complex-valued image data in the wavenumber domain is transformed into an equivalent real data problem to which Davila's algorithm is successfully applied. Two detailed illustrative examples are provided in support of the procedure. Similar reconstruction in the presence of blur as well as noise is currently under investigation.
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Bose, N.K., Kim, H.C. & Valenzuela, H.M. Recursive total least squares algorithm for image reconstruction from noisy, undersampled frames. Multidim Syst Sign Process 4, 253–268 (1993). https://doi.org/10.1007/BF00985891
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DOI: https://doi.org/10.1007/BF00985891