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Paper data
A New Two-Dimensional Fast Adaptive Filter Based on the Chandrasekhar Algorithm

Sayadi Mounir, ESSTT, Tunis
Fnaiech Farhat, ESSTT, Tunis
Mahlouthi Ahmed, ESSTT, Tunis
Chaari Abdelkader, ESSTT, Tunis
Najim Mohamed, ENSEIRB, Bordeaux

Page numbers in the proceedings:
Volume III pp 291-294

Image Representation and Transformation

Paper abstract
In this paper, a new fast algorithm for two-dimensional (2-D) linear adaptive filtering using the fast Chandrasekhar equations is presented. Using the analogy between the multichannel linear model and the 2-D one, we transform an image to a multichannel sequence and we extend the fast Chandrasekhar adaptive multichannel filtering algorithm to the 2-D case i.e. image filtering. The performance of the new 2-D adaptive filter is tested by using this filter to estimate the coefficients of a 2-D Moving Average (2-D MA) model of an unknown system. Furthermore, an application on adaptive noise cancellation of images is proposed throw a 2-D adaptive noise canceller based in the 2-D Chandrasekhar fast algorithm. Simulation results prove the superiority of the new 2-D Chandrasekhar filter comparing to similar approaches for image model identification.

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