Alten PTS, 2909 LE Capelle a/d IJssel, The Netherlands.
IEEE Trans Image Process. 2012 Feb;21(2):697-707. doi: 10.1109/TIP.2011.2165219. Epub 2011 Aug 18.
Color constancy algorithms are generally based on the simplifying assumption that the spectral distribution of a light source is uniform across scenes. However, in reality, this assumption is often violated due to the presence of multiple light sources. In this paper, we will address more realistic scenarios where the uniform light-source assumption is too restrictive. First, a methodology is proposed to extend existing algorithms by applying color constancy locally to image patches, rather than globally to the entire image. After local (patch-based) illuminant estimation, these estimates are combined into more robust estimations, and a local correction is applied based on a modified diagonal model. Quantitative and qualitative experiments on spectral and real images show that the proposed methodology reduces the influence of two light sources simultaneously present in one scene. If the chromatic difference between these two illuminants is more than 1°, the proposed framework outperforms algorithms based on the uniform light-source assumption (with error-reduction up to approximately 30%). Otherwise, when the chromatic difference is less than 1° and the scene can be considered to contain one (approximately) uniform light source, the performance of the proposed method framework is similar to global color constancy methods.
颜色恒常算法通常基于一个简化的假设，即光源的光谱分布在场景中是均匀的。然而，在现实中，由于存在多个光源，这个假设经常被违反。在本文中，我们将解决更现实的场景，其中均匀光源假设过于严格。首先，提出了一种方法，通过将颜色恒常性局部应用于图像补丁，而不是全局应用于整个图像，来扩展现有的算法。在局部（基于补丁的）光照估计之后，这些估计被组合成更稳健的估计，并基于修改后的对角模型应用局部校正。对光谱和真实图像的定量和定性实验表明，所提出的方法可以减少一个场景中同时存在两个光源的影响。如果这两个光源之间的色度差大于 1°，则所提出的框架优于基于均匀光源假设的算法（误差减少可达约 30%）。否则，当色度差小于 1°且场景可以被认为包含一个（大约）均匀的光源时，所提出的方法框架的性能与全局颜色恒常方法相似。
