Adaptive Video Block Filtering for Encoding Efficiency
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Solution Overview
Problem
Conventional image encoding/decoding methods are limited in efficiency due to restrictive filtering methods, leading to increased costs in transmitting and storing high-resolution and high-quality image data.
Innovation Solution
A method and apparatus for image encoding/decoding that dynamically determine whether to perform deblocking filtering, the filtering strength, and the number of samples used, based on the size of the current block and adjacent blocks, as well as prediction modes, to improve encoding/decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional filtering methods are used for deblocking, then the filtering process is simple to implement, but the image encoding/decoding efficiency is limited and block artifacts remain
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting filtering strength (beta and tau values) and the number of filtering samples based on block size, prediction mode, and block type (intra/inter). This allows the filtering process to adapt to different image regions and encoding conditions, improving efficiency while maintaining quality.
Solution Approach 2:
The patent implements dynamics by making the filtering process adaptive rather than static. The filtering strength and sample count are determined dynamically based on multiple factors including block size, prediction mode, and gradient calculations, allowing the system to respond to local image characteristics and optimize performance in real-time.
2Manufacturing precision
If filtering is applied to all block boundaries, then block artifacts are reduced, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by determining filtering parameters independently for each block boundary based on local characteristics such as block size, prediction mode, and gradient values. This allows different filtering strengths to be applied to different regions, improving block boundary quality where needed while reducing unnecessary filtering elsewhere.
Solution Approach 2:
The patent changes parameters locally by adjusting beta and tau values based on the specific conditions at each block boundary, including the types of blocks being filtered and their prediction modes. This localized parameter adjustment optimizes quality without uniformly increasing complexity across the entire image.
3Measurement precision
If the number of filtering samples is increased, then filtering accuracy improves, but processing time increases
Solution Approach 1:
The patent optimizes the trade-off between accuracy and time by dynamically determining the number of samples to filter based on block size and boundary characteristics. Larger blocks use more samples for better accuracy, while smaller blocks use fewer samples to reduce processing time, adapting to local requirements.
4Manufacturing precision
If deblocking filtering is performed on all boundaries, then image quality is improved, but encoding/decoding costs increase
Solution Approach 1:
The patent reduces encoding/decoding costs by applying filtering selectively based on local image characteristics. By calculating gradients and analyzing block types, the system determines which boundaries actually require filtering, avoiding unnecessary processing on boundaries where filtering would not improve quality.
Solution Approach 2:
The patent applies partial action by performing filtering only on boundaries where it is beneficial, rather than uniformly across all boundaries. The system uses gradient calculations and block type analysis to identify which boundaries need filtering, applying the filtering process partially rather than excessively.
Data Source
AI summary
An image decoding is performed by steps including: determining whether or not to perform filtering on a boundary of a current block; determining a filtering strength on the boundary of the current block, and a number of samples used in filtering; and performing filtering on the boundary of the current block on the basis of the filtering strength and the number of samples used in filtering, where the number of samples used in filtering is determined on the basis of a size of the current block.