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Bayes information criterion for Tikhonov regularization with linear constraints: application to spectral data estimation

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4 Author(s)
Carvalho, P. ; Centre for Informatics & Syst., Coimbra Univ., Portugal ; Santos, A. ; Dourado, A. ; Ribeiro, B.

Spectral data estimation is an ill-posed problem, since it is difficult to collect sufficient linear independent data and, due to the integral nature of solid-state light sensors, camera outputs do not depend continuously on input signals. To solve these problems, most methods rely on exact a priori knowledge to reduce the problem's complexity (solution space). In this paper a new algorithm is introduced which does not require a priori information. The method is build upon a new extension of the Bayes information criterion for ill-posed estimation problems, that is able to extract this information from the input data. The proposed solution is quite general and can readily be applied to other ill-posed problems, which are common in computer vision and image processing.

Published in:

Pattern Recognition, 2002. Proceedings. 16th International Conference on  (Volume:1 )

Date of Conference:

2002