Image Processing Reference

In-Depth Information

All these similarity/dissimilarity measures are based on the point-wise comparisons of the

probability density functions. As a result, they are inherently local comparison measures of

the density functions. They perform well on smooth, Gaussian-like distributions. However, on

discrete and multimodal distributions, they may not reflect the similarities and can be sensit-

ive to noises and small perturbations in data.

Example 1

Let
p
be the simple discrete distribution with a single point mass at the origin and
q
the

perturbed version with the mass shifted by
a
(
Figure 1
).

FIGURE 1
Two distributions.

The Bhatacharyya ainity and divergence values are easy to calculate:

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