Point Cloud Coding Attribute Inter Prediction Rate Distortion

The patent applies parameter changes by dynamically adjusting the attribute prediction mode (intra vs. inter prediction) based on rate-distortion optimization. The encoder evaluates different coding parameters and selects the optimal mode for each point cloud sample, changing the coding parameters adaptively to reduce bits while maintaining quality

The patent implements dynamics by making the attribute prediction mode dynamic rather than static. The coding mode is determined on-the-fly based on rate-distortion cost calculations, allowing the system to adapt to local variations in point cloud data characteristics and achieve optimal compression at each location

The patent uses parameter changes by switching between intra prediction and inter prediction modes based on rate-distortion optimization. For each point cloud sample, the encoder evaluates both modes and selects the one with lower coding cost, dynamically changing the prediction parameter to achieve the best trade-off between quality and bit rate

The patent applies local quality by allowing different prediction modes (intra or inter) to be used for different point cloud samples or regions. Instead of applying a uniform prediction mode globally, the system optimizes the prediction mode locally for each sample based on its specific characteristics and the available reference data