Adaptive Bin Buffer Management for Video Entropy Coding
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Solution Overview
Problem
Existing video compression techniques face challenges in efficiently encoding and decoding large volumes of video data due to increasing video size, resolution, and frame rate, necessitating improved encoding efficiency and image quality.
Innovation Solution
A method is provided to efficiently operate a bin buffer by restricting the bin-to-bit ratio in entropy encoding and decoding, and adaptively using various encoding/decoding methods for each basic unit, including adaptive binary arithmetic decoding and context-based adaptive binary arithmetic coding (CABAC) to manage the bin buffer effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video data is compressed using existing techniques (H.264/AVC, HEVC), then the video data can be stored or transmitted, but the encoding efficiency and image quality are insufficient for increasing video size, resolution, and frame rate
Solution Approach 1:
The patent applies dynamics by making the bin buffer size adaptive rather than fixed. The bin buffer size is dynamically adjusted based on the number of bins generated during entropy encoding, allowing the system to adapt to varying video characteristics, resolution, and frame rates. This dynamic adjustment resolves the contradiction by enabling efficient encoding across different video conditions while maintaining image quality through optimized bin buffer management.
Solution Approach 2:
The patent changes the parameter of bin buffer size from a fixed value to a variable that depends on the number of bins generated. By modifying this parameter adaptively, the system achieves better encoding efficiency for high-resolution and high-frame-rate videos while preserving image quality. The bin buffer size is adjusted based on actual encoding needs, resolving the limitations of existing compression techniques.
2Adaptability or versatility
If the bin buffer size is fixed during entropy encoding, then the encoding process is simple, but the bin-to-bit ratio cannot be optimized for different video characteristics
Solution Approach 1:
The bin buffer size is made dynamic, adjusting automatically based on the number of bins generated during encoding. This dynamic approach provides adaptability to different video characteristics without requiring complex manual configuration or multiple fixed buffer sizes, as the buffer self-adjusts during the encoding process.
Solution Approach 2:
The bin buffer management system operates autonomously by automatically adjusting its size based on the number of bins generated. The system serves itself by monitoring bin generation and adapting the buffer size accordingly, eliminating the need for external intervention or complex control mechanisms while achieving optimal bin-to-bit ratio.
3Productivity
If a single entropy encoding method is used for all blocks, then the encoding process is simple, but encoding efficiency cannot be optimized for different basic units
Solution Approach 1:
The patent applies local quality by allowing different entropy encoding methods to be used for different basic units (blocks) within the video data. Each block can be encoded using the most appropriate method based on its specific characteristics, such as motion complexity or texture patterns. This localized approach optimizes encoding efficiency for each block while maintaining overall system coherence.
Solution Approach 2:
The video data is segmented into multiple basic units or blocks, each of which can be processed with different entropy encoding methods. This segmentation allows the system to apply specialized encoding techniques to specific blocks that benefit from them, improving overall encoding efficiency without requiring a complete redesign of the encoding architecture.
Data Source
AI summary
A method is executed to efficiently operate a bin buffer to limit a bin-to-bit ratio in entropy encoding and decoding related to bitstream generation and parsing. In addition, a method of configuring a list includes various entropy encoding/decoding methods and adaptively uses the entropy encoding/decoding methods for each basic unit of entropy encoding/decoding.