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A simple non-linear system modelling algorithm designed to work with limited a priori knowledge and short data records, is examined. It creates an empirical Volterra series-based model of a system using an <alternatives>$l_{q}$<mml:math overflow="scroll"><mml:msub><mml:mi>l</mml:mi><mml:mrow><mml:mi>q</mml:mi></mml:mrow></mml:msub></mml:math><inline-graphic xlink:href="IET-CTA.2016.1360.IM1.gif" /></alternatives>...
In this paper we present a 2D stochastic model of a contrast detection autofocus, which is valid for a wide class of stochastic processes. We consider the influence of noise reduction on the focus measure function. Furthermore, we analyse formal properties of the presented autofocus algorithm along with assumptions, which have to be fulfilled by noise reduction methods.
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