Adaptive Entropy Coding Alphabet Size Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional entropy coding methods predefined alphabet sizes lead to clipping effects at high bitrates and inefficient bit usage at low bitrates, resulting in degraded reconstruction quality and coding efficiency.
Innovation Solution
Adaptive selection of entropy coding parameters, specifically the alphabet size, based on parameters carried in the bitstream, allowing the encoder to adjust encoding parameters dynamically and avoid clipping effects while optimizing bitrate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large alphabet size is used for entropy coding, then the encoder can handle wider symbol ranges without clipping, but the bitrate increases significantly and compression efficiency deteriorates
Solution Approach 1:
The patent applies dynamics by making the alphabet size adjustable rather than fixed. The encoder dynamically selects the alphabet size based on the actual range of symbols in the input data. This allows the system to adapt the coding parameters to match the data characteristics, achieving optimal compression efficiency for each specific case without unnecessary bitrate overhead from using a uniformly large alphabet size.
Solution Approach 2:
The patent implements parameter changes by varying the alphabet size parameter according to the input data's symbol range. Instead of using a predetermined large alphabet size for all cases, the system changes the alphabet size parameter to match the actual data requirements, thereby preventing both clipping errors and excessive bitrate consumption.
2Productivity
If a small alphabet size is used for entropy coding, then the compression efficiency is improved, but clipping effects occur at high bitrates leading to reconstruction quality degradation
Solution Approach 1:
The system dynamically adjusts the alphabet size based on the input data characteristics and bitrate conditions. When the data requires a wider symbol range or high bitrate conditions are present, the alphabet size is increased to prevent clipping and maintain reconstruction quality. When compression efficiency is the priority and the data fits within a smaller range, a smaller alphabet size is used to achieve better compression ratios.
Solution Approach 2:
The patent changes the alphabet size parameter adaptively based on the actual symbol range in the input data. This parameter adjustment ensures that the entropy coder uses the minimum necessary alphabet size for the given data, avoiding both the clipping effects of overly small alphabets and the bitrate overhead of unnecessarily large alphabets.
3Device complexity
If predefined entropy coding parameters are used for all input signals, then the device complexity is reduced, but the coding efficiency deteriorates due to mismatch between predefined parameters and actual data characteristics
Solution Approach 1:
The patent implements parameter changes by determining the alphabet size based on the actual range of symbols in the input data rather than using predefined values. This adaptive parameter selection improves coding efficiency by matching the entropy coding parameters to the specific characteristics of each input signal, while the determination process remains computationally efficient.
Solution Approach 2:
The system performs self-service by automatically determining the appropriate alphabet size from the input data itself. The encoder analyzes the symbol range in the input signal and selects the corresponding alphabet size without requiring external configuration or complex predefined parameter sets, thereby achieving both simplicity and efficiency.
Data Source
AI summary
Methods and apparatuses are described to encoded data into a bitstream and to decode data from a bitstream. A decoding method including: receiving a bitstream including encoded data of an input signal and a first parameter; parsing the bitstream to obtain the first parameter; obtaining an entropy coding parameter based on the first parameter; reconstructing at least a portion of the input signal, based on the entropy coding parameter and the encoded data. Due to adaptiveness of the entropy coding parameters, the optimal work of the entropy coder is possible on low bitrates which results in the bitrate saving; and the absence of clipping effect is achieved on high bitrates, which results in higher reconstruction signal quality.