Video Frame Bit Rate Allocation for Content-Adaptive Encoding
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Solution Overview
Problem
Existing image encoding technologies face challenges in effectively compressing different image frames at a consistent target bit rate, leading to varying compression performance and inefficiencies.
Innovation Solution
An image encoding method that adjusts sub-target bit rates based on image content, allocating higher rates to frames with rich information and lower rates to those with less, using a bit rate control model to adapt parameters for optimal compression and decoding precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a same target bit rate is used for compressing all image frames, then the overall video compression is simplified, but the compression performance varies significantly between different image frames
Solution Approach 1:
The patent applies local quality by differentiating compression treatment for different image frames based on their content characteristics. Frames are classified into different types (e.g., key frames, intermediate frames, redundant frames) and assigned different target bit rates accordingly. This ensures that frames with rich information content receive higher bit rates for better quality, while highly redundant frames use lower bit rates for improved compression efficiency.
Solution Approach 2:
The patent implements dynamic bit rate allocation where the target bit rate for each frame is adjusted based on real-time analysis of frame content and comparison with reference frames. The system dynamically determines compression parameters rather than using a static uniform bit rate, allowing adaptation to varying frame complexities and motion characteristics throughout the video sequence.
2Manufacturing precision
If different target bit rates are allocated to different image frames based on image content, then encoding precision and compression ratio are improved, but the encoding process complexity increases
Solution Approach 1:
The patent segments the video sequence into different frame categories (key frames, intermediate frames, redundant frames) based on content analysis. Each segment is then processed with appropriate bit rate allocation strategies. This segmentation approach simplifies the complexity by providing structured classification rather than requiring complex individual analysis of every frame, while still achieving differentiated compression optimization.
3Manufacturing precision
If high bit rate is allocated to frames with rich image content, then encoding precision is improved, but storage space requirements increase
Solution Approach 1:
The patent changes the bit rate parameter dynamically based on frame content characteristics. Frames with rich information content and high complexity are allocated higher bit rates to preserve quality, while frames with low complexity or high redundancy are allocated lower bit rates. This parameter adaptation ensures optimal use of storage space by concentrating bits where they provide maximum quality benefit and reducing bits where compression can be more aggressive.
Data Source
AI summary
An image encoding and decoding method, apparatus, and system are disclosed, and relate to the field of image encoding and decoding technologies. An encoding device adjusts a sub-target bit rate of an unencoded image frame in a video based on a target bit rate of the video, a bit rate of an encoded image frame in the video, and image content included in the unencoded image frame. For example, the encoding device allocates a high sub-target bit rate to an image frame that includes rich image content, so that a bitstream of the image frame reserves more image information. For another example, the encoding device allocates a low sub-target bit rate to an image frame that includes less image information, so that redundant image information is compressed more effectively in the image frame.