Seminario interdisciplinare
ore
14:30
presso Enriques
Basic phenomenology of human color vision has been widely taken as an inspiration to
devise
explicit color correction algorithms. The behavior of these models in terms of
significative image features (such as, e.g., contrast and dispersion)
can be difficult to characterize. To cope
with this, we propose to use a variational formulation of color contrast enhancement that
is inspired
by the basic phenomenology of color perception.
In particular, we devise a set of basic requirements to be fulfilled by an energy
to be considered as `perceptually inspired', showing that there is an explicit class
of functionals satisfying all of them. We single out
three explicit functionals that we consider of basic interest,
showing similarities and differences with existing models.
The minima of such functionals is computed using a gradient descent approach.
We also present a general methodology to reduce the computational cost
of the algorithms under analysis from ${cal O}(N2)$ to ${cal O}(Nlog N)$,
being $N$ the number of input pixels.