Some “weberized” L2-based methods of signal/image approximation

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Abstract

We examine two approaches of modifying L2-based approximations so that they conform to Weber’s model of perception, i.e., higher/lower tolerance of deviation for higher/lower intensity levels. The first approach involves the idea of intensity-weighted L2 distances. We arrive at a natural weighting function that is shown to conform toWeber’s model. The resulting “Weberized L2 distance” involves a ratio of functions. The importance of ratios in such distance functions leads to a consideration of the well-known logarithmic L2 distance which is also shown to conform to Weber’s model. In fact, we show that the imposition of a condition of perceptual invariance in greyscale space Rg ⊂ R according to Weber’s model leads to the unique (unnormalized) measure in Rg with density function ρ(t) = 1/t. This result implies that the logarithmic L1 distance is the most natural “Weberized” image metric. From this result, all other logarithmic Lp distances may be viewed as generalizations.

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APA

Kowalik-Urbaniak, I. A., La Torre, D., Vrscay, E. R., & Wang, Z. (2014). Some “weberized” L2-based methods of signal/image approximation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8814, pp. 20–29). Springer Verlag. https://doi.org/10.1007/978-3-319-11758-4_3

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