Hexagonal Intra-Prediction for Video Compression
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Solution Overview
Problem
Existing image and video compression technologies are not optimal for hexagonal sampling due to differences in primary directions and sampling geometries compared to rectangular sampling, leading to sub-optimal performance and increased prediction errors.
Innovation Solution
The implementation of intra-prediction techniques using hexagonal sampling grids, including various prediction unit shapes such as parallelogram, zigzag-square, hexagonal super-pixel, and arrow shapes, to exploit the tight-packing properties of hexagonal lattices and improve visual outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If rectangular sampling with rectangular pixel grids is used, then the processing and storage is straightforward, but the sampling efficiency is not optimal and more pixels are required compared to hexagonal sampling
Solution Approach 1:
The patent changes the sampling geometry parameter from rectangular to hexagonal grid arrangement. This parameter change enables more efficient coverage of the visual field with fewer pixels while maintaining computational tractability through adapted prediction algorithms that account for the hexagonal topology and its three primary directions
Solution Approach 2:
The patent introduces a new dimensional aspect by considering the hexagonal grid's three primary directions (0°, 60°, 120°) instead of the traditional two orthogonal directions. This dimensional expansion allows for more efficient prediction modeling that exploits the geometric properties of hexagonal sampling, reducing the number of pixels needed while maintaining processing feasibility
2Quantity of substance
If hexagonal sampling is used, then the sampling efficiency is improved and fewer pixels are required, but the existing compression technologies show sub-optimal performance due to differences in sampling geometries
Solution Approach 1:
The patent applies local quality by adapting the intra-prediction algorithm to specifically handle the hexagonal grid's unique properties. The prediction process considers the three primary directions and the tight-packing characteristics of hexagonal lattices, applying direction-specific prediction modes that exploit the local geometric structure to improve prediction accuracy and reduce errors
Solution Approach 2:
The patent addresses the asymmetric nature of hexagonal sampling compared to rectangular grids by developing prediction algorithms that explicitly account for the different geometric relationships in the three primary directions. The asymmetric connectivity pattern of hexagonal pixels (6 neighbors vs. 4 in rectangular) is leveraged to improve prediction reliability while using fewer pixels
3Device complexity
If traditional rectangular intra-prediction is applied to hexagonal sampling, then the implementation is simple, but prediction errors increase due to mismatched sampling geometries
Solution Approach 1:
The patent introduces dynamic adaptation by making the prediction algorithm sensitive to the hexagonal grid's directional properties. The algorithm dynamically selects prediction modes based on the three primary directions (0°, 60°, 120°) and adapts to the local geometric structure, allowing it to exploit the tight-packing properties of hexagonal lattices while maintaining reasonable computational complexity
Solution Approach 2:
The patent creates a universal intra-prediction framework that can handle hexagonal sampling geometry. The algorithm is designed to work with the unique properties of hexagonal grids (three primary directions, tight-packing) while maintaining compatibility with existing compression standards, achieving multi-functionality that reduces prediction errors without excessive complexity
Data Source
AI summary
Methods, systems, and devices implement intra-prediction for hexagonally-sampled compression and decompression of videos and images having a regular grid of hexagonally-shaped pixels. For encoding, a prediction unit (PU) shape is selected at a sequence level from the group consisting of parallelogram, zigzag-square, hexagonal super-pixel, a rectangular zigzag and an arrow, and the hexagonally-sampled image is divided into regions based on the PU shape. For each region: a prediction mode and a PU size are determined; reference pixels are determined for each predicted pixel in the PU shape based on the prediction mode; a weighted factor is determined for each of the reference pixels based on a distance between the reference pixel and the predicted pixel; and a predicted value of each of the predicted pixels in the PU shape is determined using the corresponding reference pixels and the weighted factors.