Entropy Escape Coding for Smaller Lossless Video Data
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Solution Overview
Problem
Existing video data compression and decompression systems face inefficiencies in entropy encoding, particularly with CABAC, which can result in larger output data sizes despite aiming for lossless compression, and there is a need for improved methods to reduce the complexity and burden of decoding processes.
Innovation Solution
The development of a data encoding and decoding apparatus that incorporates advanced entropy encoding techniques, such as modified CABAC and escape code schemes, to optimize data compression and decompression efficiency, reducing the worst-case escape code length and enhancing processing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CABAC entropy encoding is used, then lossless compression is achieved, but output data size increases
Solution Approach 1:
The patent segments the escape code into two distinct parts: a prefix portion and a suffix portion. The prefix portion encodes the most significant bits while the suffix portion encodes the least significant bits. This segmentation allows differential encoding strategies to be applied to each part, optimizing the overall code length while maintaining lossless compression capability.
Solution Approach 2:
The patent changes the encoding parameters by using a unary code for the prefix portion (encoding magnitude in terms of most significant bits) and a different code scheme for the suffix portion (encoding remaining bits). This parameter change in encoding strategy reduces the worst-case escape code length compared to traditional uniform encoding methods, thereby reducing output data size while preserving lossless compression.
2Device complexity
If traditional escape code schemes are used, then simplicity is maintained, but code length increases
Solution Approach 1:
The escape code is divided into prefix and suffix portions, where the prefix uses a simple unary code for the most significant bits and the suffix uses an optimized code for the least significant bits. This segmentation maintains relative simplicity while significantly reducing the worst-case code length compared to traditional uniform escape code schemes.
Solution Approach 2:
The encoding scheme dynamically adapts by selecting different coding strategies for different parts of the data (unary for prefix, optimized code for suffix) based on the magnitude and bit representation requirements. This dynamic approach allows the system to maintain simplicity for common cases while optimizing for worst-case scenarios, reducing overall code length.
Data Source
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AI summary
A data encoding method comprises encoding an array of data values as data sets and escape codes for values not encoded by the data sets, an escape code comprising a prefix portion and a non-unary coded suffix portion having a length, in bits, dependent upon a value encoded by the prefix portion according to a relationship such that, for at least some values encoded by the prefix portion, the length of the non-unary coded suffix portion is greater than the length, in bits, of the prefix portion.