Colour Compression of Plenoptic Point Clouds Using Raht-Klt with Prior Colour Clustering and Specular/Diffuse Component Separation

Abstract

The recently introduced plenoptic point cloud representation marries a 3D point cloud with a light field. Instead of each point being associated with a single colour value, there can be multiple values to represent the colour at that point as perceived from different viewpoints. This representation was introduced together with a compression technique for the multi-view colour vectors, which is an extension of the RAHT method for point cloud attribute coding. In the current paper, we demonstrate that the best-proposed RAHT extension, RAHT-KLT, can be improved by performing a prior subdivision of the plenoptic point cloud into clusters based on similar colour values, followed by a separation of each cluster into specular and diffuse components, and coding each component separately with RAHT-KLT. Our proposed improvements are shown to achieve better rate-distortion results than the original RAHT-KLT method.