KEYWORDS: RGB color model, Fourier transforms, Image enhancement, Colorimetry, Reflectivity, Algorithm development, Digital imaging, Human vision and color perception, Algorithms, Stochastic processes
Color constancy is a feature of the human color perception system which ensures that the perceived color of
objects remains relatively constant under varying illumination conditions, and therefore closer to the physical
reflectance. This perceptual effect, discovered by Helmholtz, was formalized by Land and McCann in 1971,
who formulated the Retinex theory. Several theories have ever since been developed, known as Retinex or color
constancy algorithms. In particular an important historic variant was proposed by Horn in 1974 and another
by Blake in 1985. These algorithms modify the RGB values at each pixel in an attempt to give an estimate of
the physical color. Land's original algorithm is both complex and not fully specified. It computes at each pixel
a stochastic integral on an unspecified set of paths on the image. For this reason, Land's algorithm has received
many recent interpretations and implementations that attempt to tune down the excessive complexity. In this
paper, a fast and exact FFT implementation of Land's, Horn and Blake theories is described. It permits for the
first time a rigorous comparison of these algorithms. A slight variant of these three algorithms will be proposed,
that makes them into contrast enhancing algorithms. Several comparative experiments on color images illustrate
the superiority of Land's model to manipulate image contrast.
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