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Recursive Partitioning Search Space Pruning Using Split Cost Prediction

: Wieckowski, A.; Ma, J.; Schwarz, H.; Marpe, D.; Wiegand, T.


Bilgin, A. ; University of Arizona; Brandeis University; Microsoft Research; IEEE Signal Processing Society:
Data Compression Conference, DCC 2019. Proceedings : Snowbird, Utah, USA, 26-29 March 2019
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-72810-657-1
ISBN: 978-1-72810-658-8
Data Compression Conference (DCC) <2019, Snowbird/Utah>
Fraunhofer HHI ()

One of the innovations in H.265/HEVC is the quad-tree partitioning framework. It allows flexible block subdivision and mode allocation across the encoded picture. The increased flexibility comes at a cost of vast search space expansion, making exhaustive search algorithms inapplicable. We propose a novel early termination condition to skip the exhaustive search of whole tree-branches in the well-established top-down encoding approach. The condition is based on a simple and intuitive split cost prediction. It can be parametrized to control the trade-off between the speed-up and caused BD-rate loss. Data driven parameter estimation and parameter number reduction is presented. For random-access encoding, the method can achieve an average speed-up of 30% with a BD-rate loss of 0.03%. At another trade-off point, speed-up is increased to over 40% for a BD-rate loss below 0.5%.