Adaptive Video Encoder GOP Structure Optimization
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Solution Overview
Problem
Existing video encoding technologies face limitations in adaptively adjusting the structure of a group of pictures (GOP) based on input picture characteristics, leading to suboptimal coding efficiency and performance, especially during scene changes.
Innovation Solution
A method and system for encoding video data that involves dividing input pictures into subgroups, generating candidate encoded groups using independent encoding schemes, and selecting the optimal encoded pictures based on coding cost and quality parameters, allowing for adaptive adjustment of the GOP structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed GOP structure is used for video encoding, then the encoding process is simple and fast, but the coding efficiency and performance are suboptimal, especially during scene changes
Solution Approach 1:
The patent implements dynamic GOP structure adjustment by allowing the encoder to adaptively change GOP parameters (such as GOP size, picture type distribution, and subgroup configurations) based on real-time analysis of input picture characteristics like scene changes, motion intensity, and content complexity. This transforms the static GOP structure into a dynamic one that responds to content variations, thereby improving coding efficiency without requiring fundamentally complex encoding architecture.
Solution Approach 2:
The patent changes encoding parameters adaptively by adjusting GOP structure parameters (e.g., number of I-frames, P-frames, B-frames, subgroup sizes) based on detected picture characteristics. When scene changes are detected, the encoder modifies parameters such as increasing I-frame frequency or adjusting subgroup configurations to optimize compression for the new content type, thus resolving the contradiction between simple fixed-structure encoding and efficient adaptive encoding.
2Productivity
If multiple candidate encoded groups are generated and compared based on coding cost and quality parameters, then the coding performance is optimized, but the encoding time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-generating multiple candidate encoded groups for each subgroup before final selection. These candidates are created using different encoding schemes (e.g., varying picture types, prediction modes, or quantization parameters) and stored in a buffer pool. This preliminary generation allows the encoder to have ready-made options for quick comparison and selection based on coding cost and quality metrics, optimizing performance while managing encoding time through structured pre-computation.
Solution Approach 2:
The patent implements partial action by generating a limited number of carefully selected candidate encoded groups rather than exhaustively encoding all possible combinations. The encoder focuses on generating a manageable set of promising candidates (e.g., 2-5 per subgroup) based on heuristic rules or simplified evaluations, then compares these partial candidates using coding cost and quality parameters. This approach achieves good coding performance without the prohibitive computational cost of exhaustive search.
3Productivity
If the GOP structure is adaptively adjusted based on input picture characteristics, then the coding efficiency improves, but the device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the GOP into multiple subgroups (e.g., first subgroup, second subgroup, etc.) that can be independently encoded and optimized. Each subgroup can have its own encoding parameters and picture type assignments, allowing fine-grained adaptive adjustment without requiring complex global optimization. This segmentation simplifies the adjustment process by breaking down the complex GOP structure into manageable, independently controllable units that respond to local picture characteristics.
Data Source
AI summary
A device that may implement a video encoder may include generating a video display that includes groups of encoded pictures selected based on comparisons between different groups of encoded pictures that are generated according to separate, independent encoding schemes. Input pictures may include multiple subgroups of one or more input pictures. Each subgroup of pictures may be encoded multiple times, according to separate, independent encoding schemes to generate multiple candidate encoded groups associated with each subgroup. For each subgroup, one candidate encoded group may be selected as encoded pictures associated with the subgroup. The selected encoded pictures may be used to generate a video display that includes the encoded pictures associated with the plurality of subgroups.