Rice Parameter Derivation via Quantization in Video Coding
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, particularly in fields like virtual reality and ultra-high definition, necessitates a highly efficient compression technique to reduce transmission and storage costs, as existing methods are inadequate in efficiently encoding and decoding such content.
Innovation Solution
A method and apparatus for enhancing video/image coding efficiency by deriving a Rice parameter for transform coefficients based on quantization parameters, allowing for improved bin string derivation and level value extraction, which is applied in both encoding and decoding processes without additional lookup tables or signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional encoding methods are used for high-resolution video, then transmission and storage costs increase, but compression efficiency remains insufficient
Solution Approach 1:
The patent changes the parameter used for Rice parameter derivation from traditional block-size-based methods to quantization parameter (QP)-based methods. By using QP values (which reflect the actual compression intensity applied to coefficients) to derive Rice parameters, the encoding adapts dynamically to the local compression requirements, improving compression efficiency while reducing the bitstream size for high-resolution content
2Productivity
If existing Rice parameter derivation methods are used, then coding efficiency is limited, but the method lacks adaptability to different quantization levels
Solution Approach 1:
The patent derives Rice parameters by applying a function to quantization parameter values. Specifically, it uses formulas such as rice_parameter = floor((qp + offset) / scale) or similar QP-based transformations, allowing the Rice parameter to adapt automatically to different quantization levels. This creates a direct link between the quantization intensity and the entropy coding parameters, improving both efficiency and adaptability across various compression scenarios
Solution Approach 2:
The patent establishes a feedback mechanism where the quantization parameter (which determines coefficient magnitude distribution) feeds into the Rice parameter derivation. This creates an adaptive loop where the entropy coding parameters are continuously adjusted based on the actual quantization applied, allowing the system to optimize coding efficiency for each local region's characteristics
3Productivity
If additional lookup tables or signaling are used to improve coding performance, then device complexity increases
Solution Approach 1:
The patent makes the system self-service by deriving Rice parameters automatically from existing quantization parameters without requiring external lookup tables or additional signaling. The QP values, which are already computed during the transformation and quantization stages, are directly reused to determine Rice parameters, eliminating the need for separate parameter transmission or complex table structures while maintaining high coding performance
Data Source
AI summary
A video decoding method performed by a decoding apparatus according to the present document may comprise the steps of: acquiring, from a bitstream, information indicating a level value of a transform coefficient in a current block; deriving a Rice parameter for the information indicating the level value of the transform coefficient, on the basis of a quantization parameter of the current block; deriving a bin string for the information indicating the level value of the transform coefficient, on the basis of the Rice parameter; and deriving the level value of the transform coefficient on the basis of the bin string.