A fast multichannel approach to adaptive image estimation

A computationally efficient method for adaptive image estimation is developed, based on the multichannel form of the one-dimensional fast least-squares algorithms. Extended forms of various two-dimensional autoregressive image models are derived and used for this purpose. It is shown that the method, named the fast multichannel space recursive estimation technique (FAMSRET), can overcome image boundary discontinuity problems by processing consecutive image lines in opposite directions. Two-dimensional instrumental variables are introduced and used by the FAMSRET algorithm for the efficient estimation of images, which are degraded by additive white noise. Examples are given that illustrate the performance of the proposed techniques. >

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