Adaptive Filter Shape Switching for Video Sample Reconstruction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently reducing redundancy in video signals, particularly in adapting filter shapes for optimal sample offset and compression efficiency.
Innovation Solution
The implementation of non-linear mapping based filters with adaptive filter shape configurations, such as cross-component sample offset (CCSO) and local sample offset (LSO) filters, which switch between different filter shapes based on decoded indices to optimize sample reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fixed filter shapes are used for sample offset, then the implementation is simple, but the compression efficiency is insufficient
Solution Approach 1:
The patent applies dynamics by enabling the filter shape to change adaptively based on the sample offset value. Instead of using a fixed filter shape, the system dynamically switches between different filter shapes (e.g., horizontal, vertical, diagonal) depending on the magnitude and direction of the sample offset, allowing optimal filtering for different compression scenarios
Solution Approach 2:
The patent changes the parameter of filter shape configuration based on the sample offset characteristics. By monitoring the sample offset value and adjusting the filter shape parameter accordingly, the system optimizes the balance between filtering effectiveness and compression efficiency for different video content types
2Productivity
If multiple filter shapes are implemented for optimal sample offset, then the compression ratio improves, but the computational complexity increases
Solution Approach 1:
The patent applies local quality by selecting different filter shapes tailored to specific local conditions in the video data. Instead of using a single filter shape for the entire image, the system analyzes local characteristics (such as edge orientation and sample offset magnitude) and applies the most appropriate filter shape to each region, optimizing compression locally without requiring complex global computation
Solution Approach 2:
The system changes filter shape parameters based on local sample offset characteristics. By adjusting the filter shape parameter according to the magnitude and direction of sample offsets in different regions, the patent achieves higher compression ratios while controlling computational complexity through parameter-based adaptation rather than complex structural changes
3Productivity
If filter shape switching is added to enhance coding efficiency, then the compression performance improves, but the decoding time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining a set of candidate filter shapes and their corresponding configurations before the decoding process. The system pre-calculates and stores filter shape parameters, allowing the decoder to quickly select and apply the appropriate filter shape based on the sample offset value without performing complex real-time computations, thus reducing decoding time
Data Source
AI summary
Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. An example method of video decoding includes receiving a video bitstream and reconstructing a first sample of the video bitstream using a non-linear mapping-based filter with a first filter shape configuration of a plurality of filter shape configurations. The plurality of filter shape configurations includes at least two filter shape configurations that are based on a same geometric shape and include a same number of filter taps, and the filter taps of the at least two filter shape configurations are located at different positions. The method further includes selecting a second filter shape configuration of the plurality of filter shape configurations, and reconstructing a second sample in the video based on the non-linear mapping-based filter with the second filter shape configuration.