Improvement of aperiodic models of deconvolution using an extended size deconvolution method

This paper proposes a methodology for estimating the restoration filter of a degraded image by using an iterative approach involving spatial deconvolu tion in an aperiodic restoration model environment. This methodology consis ts of an improvement to the generic aperiodic restoration model, based on o perating with a truncated blurring matrix to generate a restoration filter by means of iterations. As a result, we have the operational advantages of the circulant model besides of better restoration results than using the pu re aperiodic model in noisy conditions, therefore, there is a reduction of the condition number of the matrices involved for the usual values for the filter mask found in the literature. Some tests have been carried out to va lidate the proposed model, adding different quantities of gaussian noise to the degraded image. Comparisons have been made between the generic aperiod ic model, the circulant model, and the improved aperiodic model proposed in this paper, using the restoration filters in an approach to the Wiener res toration scheme. The results obtained with the improved aperiodic model pro posed in this paper show ISNR improvements both with respect to the generic aperiodic model and the circulant model. (C) 2001 Elsevier Science B.V. Al l rights reserved.