CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2009 vol.31 Issue No.03 - March

Subscribe

Issue No.03 - March (2009 vol.31)

pp: 458-474

Edoardo Provenzi , Università di Milano, Crema

Rodrigo Palma-Amestoy , Universidad de Chile , Santiago

Vincent Caselles , Universitat Pompeu Fabra, Barcelona

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.86

ABSTRACT

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 O(N2) to O(N logN), being N the number of pixels of the input image.

INDEX TERMS

Constrained optimization, Gradient methods, Partial Differential Equations, Iterative solution techniques, Enhancement, Filtering, Color

CITATION

Edoardo Provenzi, Rodrigo Palma-Amestoy, Vincent Caselles, "A Perceptually Inspired Variational Framework for Color Enhancement",

*IEEE Transactions on Pattern Analysis & Machine Intelligence*, vol.31, no. 3, pp. 458-474, March 2009, doi:10.1109/TPAMI.2008.86REFERENCES