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We propose an intra frame predictive strategy for compression of 3D pointcloud attributes. Our approach is integrated with the region adaptive graphFourier transform (RAGFT), a multi-resolution transform formed by a compositionof localized block transforms, which produces a set of low pass (approximation)and high pass (detail) coefficients at multiple resolutions. Since thetransform operations are spatially localized, RAGFT coefficients at a givenresolution may still be correlated. To exploit this phenomenon, we propose anintra-prediction strategy, in which decoded approximation coefficients are usedto predict uncoded detail coefficients. The prediction residuals are thenquantized and entropy coded. For the 8i dataset, we obtain gains up to 0.5db ascompared to intra predicted point cloud compresion based on the region adaptiveHaar transform (RAHT).

Multi-resolution intra-predictive coding of 3D point cloud attributes