Adaptive Wiener Filter Shape for Video Compression
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Solution Overview
Problem
Current video compression technologies face inefficiencies in adapting filter shapes for Wiener-based filters, leading to suboptimal compression performance due to the use of fixed filter shapes that do not consider the relationship between input and center samples.
Innovation Solution
The implementation of an adaptive Wiener-based filter shape that dynamically adjusts its configuration based on the relationship between the to-be-filtered sample and input samples, allowing for a modified filter shape to be determined and applied, which can include marking outliers and adjusting filter coefficients accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed filter shape is used for Wiener-based filter, then the device complexity is reduced, but the compression performance deteriorates due to inability to adapt to different sample relationships
Solution Approach 1:
The filter shape is made dynamic by determining a modified filter shape based on the relationship between the to-be-filtered sample and input samples. The system transitions from a static fixed filter shape to a dynamic adaptive filter shape that changes according to the statistical characteristics of the input data, thereby improving compression performance while managing complexity through data-driven adaptation.
Solution Approach 2:
The invention changes the parameter of filter shape from a fixed configuration to a variable one that adapts based on sample relationships. By modifying the filter shape parameters according to the relationship between center samples and input samples, the system optimizes compression efficiency for different video content characteristics without requiring a completely complex reconfiguration system.
2Productivity
If an adaptive filter shape is implemented, then compression efficiency is improved, but the processing time increases due to additional calculations for determining modified filter shapes
Solution Approach 1:
The system performs preliminary analysis of the relationship between to-be-filtered samples and input samples to determine the appropriate filter shape before actual filtering occurs. By pre-determining the modified filter shape based on sample relationships, the system optimizes the filtering process and avoids unnecessary calculations during the main compression task, thereby improving efficiency while controlling processing time.
Solution Approach 2:
The adaptive filter shape utilizes feedback from the relationship analysis between input samples and center samples to adjust the filter configuration. This feedback mechanism allows the system to continuously optimize the filter shape based on actual data characteristics, improving compression efficiency while maintaining processing time within acceptable limits through intelligent adaptation.
3Manufacturing precision
If fixed filter shape is used, then the ease of operation is maintained, but the quality of filtered output deteriorates due to lack of adaptation to specific sample characteristics
Solution Approach 1:
The filter system performs self-service by automatically determining the appropriate filter shape based on the relationship between input samples and center samples. Instead of requiring manual configuration or complex user input, the system autonomously adapts the filter shape to match the specific characteristics of the input data, thereby improving output quality while maintaining ease of operation through automated adaptation.
Solution Approach 2:
The invention automatically changes the filter shape parameters based on the statistical relationship of the input samples. This automated parameter adjustment eliminates the need for manual filter configuration while significantly improving the quality of filtered output. The system adapts the filter shape to the specific characteristics of each input sample, achieving high precision without increasing operational complexity.
Data Source
AI summary
Some aspects of the disclosure provide a method of video decoding. The method includes: receiving a bitstream that comprises coded information of one or more pictures; generating, according to the bitstream, at least a to-be-filtered sample, and input samples for filtering the to-be-filtered sample in an in-loop filter, the in-loop filter using a Wiener-based filter with an adaptive filter shape; determining a modified filter shape for the Wiener-based filter, the modified filter shape being adapted according to a relationship between the to-be-filtered sample and the input samples; and applying the Wiener-based filter with the modified filter shape on the input samples to generate a filtered output of the to-be-filtered sample.