Recursive implementation of total least squares algorithm for image reconstruction from noisy, undersampled multiframes

Authors:
N. K. Bose;H. C. Kim;H. M. Valenzuela
Affiliations:
Spatial and Temporal Signal Processing Center, Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park;Spatial and Temporal Signal Processing Center, Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park;Spatial and Temporal Signal Processing Center, Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Year:
1993

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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. Computer simulations are provided in support of the procedure.