In 1964 Edwin H. Land formulated the Retinex theory, the first attempt to simulate and explain how the human visual system perceives color. Unfortunately, the Retinex Land-McCann original algorithm is both complex and not fully specified. Indeed, this algorithm computes at each pixel an average of a very large set of paths on the image. For this reason, Retinex has received several interpretations and implementations which, among other aims, attempt to tune down its excessive complexity. But, Morel et al. have shown that the original Retinex algorithm can be formalized as a (discrete) partial differential equation. This article describes the PDE-Retinex, a fast implementation of the Land-McCann original theory using only two DFT's. The source code, the code documentation, and the online demo are accessible at the IPOL web part of this article 1 . In this link an implementation is available for download. Compilation and usage instruction are included in the README.txt file of the compressed archive. Keywords: PDE; Retinex; color In 1964 Edwin H. Land [1] formulated the Retinex theory, the first attempt to simulate and explain how the human visual system perceives color. His theory and an extension, the "reset Retinex" [2] were further formalized by Land and McCann in 1971. Several Retinex algorithms have been developed ever since. These color constancy algorithms modify the RGB values at each pixel to give an estimate of the physical color independent of the shading. The Retinex original method was complex and imprecise. Indeed, this algorithm computes at each pixel an average of a very large and unspecified set of paths on the image. For this reason, Retinex has received several interpretations and implementations which, among other aims, attempt to tune down its excessive complexity.
In a similar direction, Limare et al. REF proposed an implementation in the Fourier domain of the Retinex 3 algorithm as a Poisson Equation with Neumann boundary conditions.
Retinex Poisson Equation: a Model for Color Perception
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