Color consistency correction for color point clouds is a fundamental yet important task in 3D rendering and compression applications. In the past, most previous color correction methods aimed at correcting color for color images. The purpose of this paper is to propose a grouping-based hybrid color correction algorithm for color point clouds. Our algorithm begins by estimating the overlapping rate between the aligned source and target point clouds, and then adaptively partitions the target points into two groups, namely the close proximity group Gcl and the moderate proximity group Gmod, or three groups, namely Gcl, Gmod, and the distant proximity group Gdist, when the estimated overlapping rate is low or high, respectively. To correct color for target points in Gcl, a K-nearest neighbors based bilateral interpolation (KBI) method is proposed. To correct color for target points in Gmod, a joint KBI and the histogram equalization (JKHE) method is proposed. For target points in Gdist, a histogram equalization (HE) method is proposed for color correction. Finally, we discuss the grouping-effect free property and the ablation study in our algorithm. The desired color consistency correction benefit of our algorithm has been justified through 1086 testing color point cloud pairs against the state-of-the-art methods. The C++ source code of our algorithm can be accessed from the website: https://github.com/ivpml84079/Point-cloud-color-correction.

翻译：彩色点云的颜色一致性校正是三维渲染与压缩应用中的基础且重要任务。以往大多数色彩校正方法主要针对彩色图像进行校正。本文旨在提出一种基于分组的混合色彩校正算法用于彩色点云。该算法首先估计对齐的源点云与目标点云之间的重叠率，然后根据估计的重叠率高低，自适应地将目标点划分为两组（即近距离组Gcl与中距离组Gmod）或三组（即Gcl、Gmod及远距离组Gdist）。为校正Gcl中目标点的颜色，提出了一种基于K近邻的双边插值（KBI）方法。为校正Gmod中目标点的颜色，提出了一种联合KBI与直方图均衡化（JKHE）的方法。对于Gdist中的目标点，则采用直方图均衡化（HE）方法进行色彩校正。最后，本文讨论了算法的无分组效应特性与消融实验。通过对1086组测试彩色点云对与现有先进方法的对比，验证了本算法在颜色一致性校正方面的预期优势。算法的C++源代码可从网站https://github.com/ivpml84079/Point-cloud-color-correction获取。