Bertalmío Marcelo, Caselles Vicent, Provenzi Edoardo, Rizzi Alessandro
Departament de Tecnologia, Universitat Pompeu Fabra, 08003 Barcelona, Spain.
IEEE Trans Image Process. 2007 Apr;16(4):1058-72. doi: 10.1109/tip.2007.891777.
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.
在本文中，我们在变分技术框架下对数字图像基于感知的色彩校正展开讨论。我们提出一种新颖的图像泛函，其最小化会生成一个受感知启发的原始图像色彩增强版本。变分公式允许对对比度调整进行更灵活的局部控制并与数据相结合。我们表明，应用于该能量泛函的梯度下降技术的数值实现与自动色彩增强（ACE）方程一致，ACE是一种特定的基于感知的色彩增强模型。此外，我们证明，欧拉 - 拉格朗日方程的数值近似将ACE的计算复杂度从θ(N²)降低到θ(N log N)，其中N是图像中的像素总数。
