Abstract

We are concerned with the construction of “Weberized” metrics for image functions – distance functions which allow greater deviations at higher intensity values and lower deviations at lower intensity values in accordance with Weber’s models of perception. In this paper, we show how the use of appropriate nonuniform measures over the image function range space can be used to produce “Weberized” metrics. In the case of Weber’s standard model, the resulting metric is an \(L^1\) distance between logarithms of the image functions. For generalized Weber’s law, the metrics are \(L^1\) distances between appropriate powers of the image functions. We then define the corresponding \(L^2\) analogues of these metrics which are easier to work with because of their differentiability properties. Finally, we extend the definition of these “Weberized” metrics to vector-valued functions.

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