Image Decoding With Triangular Partition Motion Prediction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently processing increasing amounts of digital video data, particularly in inter and intra prediction functions, with a need for improved encoding and decoding efficiency and speed, especially in handling non-rectangular shaped partitions.
Innovation Solution
The implementation of image block splitting into a plurality of partitions, including non-rectangular shapes such as triangles, along with adaptive filtering and motion vector refinement techniques, enhances encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video coding technology processes increasing amounts of digital video data using traditional rectangular block partitions, then processing capability is maintained at existing levels, but encoding efficiency and processing speed improve
Solution Approach 1:
The image block is divided into multiple partitions including non-rectangular shapes (triangles, trapezoids) in addition to traditional rectangular blocks. This segmentation allows the coding system to adapt to different geometric shapes in video content, improving encoding efficiency by better matching the actual structure of video data while maintaining manageable processing complexity through systematic handling of each partition type.
Solution Approach 2:
The patent introduces new parameters to define non-rectangular partition shapes, such as triangle partitions defined by three vertices and trapezoid partitions defined by four vertices. These parameter changes enable the coding system to represent and process diverse geometric shapes, thereby improving encoding efficiency without excessively increasing device complexity through standardized parameter sets.
2Productivity
If non-rectangular partitions are introduced to improve encoding efficiency, then encoding efficiency increases, but processing speed decreases
Solution Approach 1:
By segmenting the image block into multiple partition types (rectangular, triangular, trapezoidal), the system can process different regions with appropriate methods. This segmentation improves encoding efficiency by better fitting the partition shapes to video content structures while maintaining processing speed through efficient algorithms for each partition type.
Solution Approach 2:
Different partition shapes are applied to different regions of the image block based on local content characteristics. This local quality approach allows the system to optimize encoding efficiency in regions where non-rectangular shapes are beneficial while using simpler rectangular partitions in other regions, thereby balancing encoding efficiency improvement with processing speed maintenance.
3Manufacturing precision
If non-rectangular partitions are used to better represent video content, then manufacturing precision of video coding improves, but device complexity increases
Solution Approach 1:
The image block is segmented into multiple partition types including triangles and trapezoids alongside rectangles. This segmentation improves video coding precision by allowing more accurate representation of video content geometry while controlling device complexity through a finite set of standardized partition types and their associated parameters.
Solution Approach 2:
The patent defines specific parameters for non-rectangular partitions (e.g., three vertices for triangles, four vertices for trapezoids) to precisely represent their geometry. These parameter changes enable accurate video coding representation while managing device complexity by using a structured and limited parameter set that can be systematically processed.
Data Source
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AI summary
An image encoder is provided, which includes circuitry and a memory coupled to the circuitry. The circuitry, in operation, performs: splitting an image block into a plurality of partitions including a first partition having a non-rectangular shape (e.g., a triangular shape) and a second partition; predicting a first motion vector for the first partition and a second motion vector for the second partition; and encoding the first partition using the first motion vector and the second partition using the second motion vector.