Block Partition Blending for Triangular Video 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, especially when image blocks are split into non-rectangular shapes like triangles, leading to inefficiencies in encoding and decoding processes.
Innovation Solution
Implementing a boundary smoothing operation that predicts and weights pixel values of triangular partitions using motion vectors, followed by decoding or encoding these partitions to enhance encoding efficiency and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image blocks are split into non-rectangular partitions (triangles), then the ability to represent complex image structures is improved, but the encoding and decoding complexity increases
Solution Approach 1:
The image block is divided into multiple triangular partitions, each processed independently with its own motion vector and prediction values. This segmentation allows complex image structures to be represented through simple triangular units, reducing overall processing complexity while maintaining representational flexibility.
Solution Approach 2:
Different weighting schemes are applied to different regions along the boundary between partitions. First values and second values are weighted differently based on their proximity to the boundary, with weights varying locally to optimize prediction accuracy for each specific region rather than applying a uniform approach.
2Measurement precision
If boundary smoothing operation with weighting is applied between partitions, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The boundary smoothing operation is applied selectively only to pixels along the boundary between partitions, rather than to the entire image block. This partial application reduces processing time while still achieving improved prediction accuracy where it is most needed—at the partition boundaries.
Solution Approach 2:
The weighting parameters are designed to transition smoothly from one value to another along the boundary, creating a continuous blending effect. This parameter variation approach achieves high prediction accuracy by accounting for the gradual change in partition influence, while the predefined weighting scheme keeps computation efficient.
3Productivity
If motion vectors are used for predicting pixel values in triangular partitions, then inter prediction efficiency is improved, but handling non-rectangular shapes becomes more difficult
Solution Approach 1:
The use of motion vectors is applied independently to each triangular partition rather than attempting to handle the entire non-rectangular block as a single unit. This segmentation simplifies the mathematical operations required for motion compensation, as each triangle can be processed with standard motion vector techniques, reducing overall complexity while maintaining inter prediction efficiency.
Data Source
AI summary
An image decoder includes circuitry and a memory, wherein the circuitry, in operation, calculates first values of a first partition in a current block, using a first motion vector for the first partition; calculates second values of a second partition in the current block, using a second motion vector for the second partition; calculates third values of a set of pixels between the first partition and the second partition, using the first motion vector; calculates fourth values of the set of pixels, using the second motion vector; and weights the third values and the fourth values. A number of pixels in a row in the set of pixels is two or more, and two or more weights applied to the third values increase along the row.