Optical EngineeringEfficient retrieval of the regularized least squares solution
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An adaptive approach to the recovery of the least-squares (LS) solution employing regularization and conjugate gradient descent is developed. This is then implemented on image data corrupted by deterministic blur and additive Gaussian noise. The approach is useful where large data vectors are being processed with the need to conserve space and obtain reliable estimates rapidly.