Maximum a posteriori restoration of blurred images using self-organization

Cheng-Yuan Liou; Wen-Pin Tai

doi:10.1117/1.482628

1 January 1998 Maximum a posteriori restoration of blurred images using self-organization

Cheng-Yuan Liou, Wen-Pin Tai

Journal of Electronic Imaging, Vol. 7, Issue 1, (January 1998). https://doi.org/10.1117/1.482628

We use the "magic TV" network with the maximum a posteriori (MAP) criterion to restore a space-dependent blurred image. This network provides a unique topological invariance mechanism that facilitates the identification of such space-dependent blur. Instead of using parametric modeling of the underlying blurred image, we use this mechanism to accomplish the restoration. The restoration is reached by a self-organizing evolution in the network, where the weight matrices are adapted to approximate the blur functions. The MAP criterion is used to indicate the goodness of the approximation and to direct the evolution of the network.

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Cheng-Yuan Liou and Wen-Pin Tai "Maximum a posteriori restoration of blurred images using self-organization," Journal of Electronic Imaging 7(1), (1 January 1998). https://doi.org/10.1117/1.482628

Published: 1 January 1998

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