Perceptual color correction through variational techniques.
In this paper, we present a discussion about perceptual-based color correction of digital images in the framework of variational techniques. We propose a novel image functional whose minimization produces a perceptually inspired color enhanced version of the original. The variational formulation permits a more flexible local control of contrast adjustment and attachment to data. We show that a numerical implementation of the gradient descent technique applied to this energy functional coincides with the equation of automatic color enhancement (ACE), a particular perceptual-based model of color enhancement. Moreover, we prove that a numerical approximation of the Euler-Lagrange equation reduces the computational complexity of ACE from theta(N2) to theta(N log N), where N is the total number of pixels in the image.
Bertalmío
Marcelo
M
Departament de Tecnologia, Universitat Pompeu Fabra, 08003 Barcelona, Spain. marcelo.bertalmio@upf.edu
Caselles
Vicent
V
Provenzi
Edoardo
E
Rizzi
Alessandro
A
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D003116:Color; D003118:Color Perception; D003124:Colorimetry / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity