Adaptive Dependent Quantization Decoder State Transition
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently supporting multiple variants of dependent quantization, leading to increased implementation complexity and reduced coding efficiency due to the need for separate decoding processes for different quantization modes.
Innovation Solution
A unified framework is introduced that supports independent quantization and multiple variants of dependent quantization, allowing for adaptive selection of quantization modes and state transition tables, enabling efficient decoding and encoding of transform coefficient levels with reduced complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple variants of dependent quantization are supported, then coding efficiency is improved, but decoder implementation complexity increases
Solution Approach 1:
The patent implements a universal decoder architecture that can handle multiple quantization variants (4-state and 8-state DQM, and independent quantization) through a single unified state transition framework. The decoder uses a generic state transition table structure that can be configured for different variants, allowing one decoder implementation to support all quantization modes without requiring separate decoding paths for each variant.
Solution Approach 2:
The patent resolves the complexity issue by parameterizing the state transition behavior through configurable transition tables. The same decoder architecture adapts to different quantization variants by changing the state transition parameters (the transition tables themselves) rather than changing the fundamental decoding logic. This allows the decoder to support multiple variants while maintaining a single, relatively simple implementation.
2Productivity
If the number of quantization states is increased, then coding efficiency is improved, but encoder complexity increases
Solution Approach 1:
The patent implements dynamic state transition mechanisms where the quantization state evolves adaptively during the encoding process based on the transform coefficient data. The encoder uses state transition tables that dynamically determine the next state based on current state and input data characteristics, allowing the system to adapt to different signal patterns without requiring complex manual configuration for each encoding scenario.
Solution Approach 2:
The patent manages encoder complexity by parameterizing the quantization behavior through configurable state transition tables. The encoder complexity is controlled by changing parameters (the transition tables) rather than changing the fundamental encoding architecture. This allows support for multiple quantization variants (4-state, 8-state) while maintaining a unified, manageable encoder implementation.
3Measurement precision
If separate decoding processes are used for different quantization modes, then decoding accuracy is maintained, but implementation complexity increases
Solution Approach 1:
The patent merges multiple separate decoding processes into a single unified decoding architecture. Instead of implementing distinct decoders for 4-state DQM, 8-state DQM, and independent quantization, the patent combines all these functions into one decoder that uses a unified state transition framework. The unified process selects and applies the appropriate transition behavior based on the quantization mode, eliminating the need for separate decoding paths while maintaining accuracy for all variants.
Data Source
AI summary
A decoder configured to decode residual levels, and sequentially dequantize the residual levels by selecting a quantizer out of a set of default quantizers depending on a current transition state, and updating the current transition state depending on a current residual level's characteristic obtained by an application of a binary function onto the current residual level, and depending on a quantization mode information contained in the data stream. The current transition state transitions, according to a surjective mapping which depends on the quantization mode information, from a domain of combinations of a set of one or more transition states with the current residual level's characteristic onto the set of one or more transition states, wherein a cardinality of the set of one or more transition states differs depending on the quantization mode information.