Titlebook: Computer Analysis of Images and Patterns; 8th International Co Franc Solina,Alešs Leonardis Conference proceedings 1999 Springer-Verlag Ber

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happiness

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https://doi.org/10.1007/978-3-319-01715-0lse using some well-known restoration techniques, e.g. the Wiener filtering, constraint restoration, entropy restoration, and Baysian restoration. The used restoration techniques imply the robustness of the presented method. Our approach is a generalization of the matched filtering approach. Additio

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掺假

https://doi.org/10.1007/978-3-658-15754-8fact, there exists no measure that indicates whether a given database is sufficient to train and/or to test a given algorithm. This paper proposes a method to rank the complexity of databases, respectively to validate whether a database is appropriate for the simulation of a given application. The f

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Susanne Moser,Hans-Walter Ruckenbauers able to reduce the amount of image data in dependence of the image context. Within the important image regions nearly no image data will be reduced. The image data of the unimportant image regions are reduced in a very strong way. The data reduction factors for the important and the unimportant im

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