Block Partitioning for Accurate Intra-Prediction With Low Signaling
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Solution Overview
Problem
Existing block-based codecs face challenges in achieving high coding efficiency due to the trade-off between signaling overhead and prediction accuracy, particularly in intra-prediction, where larger blocks result in less accurate spatial prediction and increased signaling overhead.
Innovation Solution
The proposed solution involves partitioning a block into multiple partitions along a specific dimension, allowing for sequential reconstruction using neighboring samples to derive a predictor and correct it with a prediction residual, thereby reducing signaling overhead while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If larger blocks are used for intra-prediction, then signaling overhead is reduced, but prediction accuracy deteriorates
Solution Approach 1:
The patent divides a large block into multiple smaller partitions (e.g., 4 partitions) along a specific direction. Each partition is then predicted separately using intra-prediction modes. This segmentation allows the system to maintain lower signaling overhead by using a coarse granularity for mode signaling while achieving higher prediction accuracy through finer local adaptation in each partition.
2Measurement precision
If more intra-prediction modes are supported, then prediction accuracy improves, but signaling overhead increases
Solution Approach 1:
The patent applies different intra-prediction modes to different partitions based on local characteristics. Each partition can be assigned an intra-prediction mode independently, allowing the system to adapt to local image features while maintaining a manageable signaling overhead by limiting the number of modes signaled per partition.
3Measurement precision
If blocks are subdivided into more partitions, then prediction accuracy improves, but device complexity increases
Solution Approach 1:
The patent subdivides blocks into a limited number of partitions (e.g., 4 partitions per block) rather than excessive segmentation. This moderate level of subdivision achieves improved prediction accuracy by capturing local variations while avoiding excessive processing complexity that would result from finer-grained partitioning.
Data Source
AI summary
Block-based coding of a picture is rendered more effective by providing an intra-prediction coding concept according to which a certain block of the picture is intra-prediction coded using a certain intra-coding mode by partitioning the predetermined block into partitions along a certain dimension with the number of partitions being greater than two and/or the partitions being one sample wide along the certain dimension with the partitions being, for reconstruction purposes, sequentially subject to spatial prediction using the intra-prediction coding mode signaled for the certain block followed by correcting the thus obtained predictor using a prediction residual so that for preceding partitions a reconstruction of the samples is available to the decoder at the time of processing the next, then current, partition. Signaling overhead with respect to the partitioning may be left off or may be kept low.