Luma Weighting Factor Encoding With Fixed-Point Difference Coding
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Solution Overview
Problem
Conventional image encoding methods, such as H.264, face challenges in representing weighting factors with predetermined bit precision, leading to inefficiencies in coding efficiency.
Innovation Solution
An encoding device and method that derive a first reference value based on fixed point precision, encode a first difference value between the weighting factor and the reference value, ensuring the difference falls within a predetermined bit precision range, thereby improving coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a weighting factor is represented with predetermined bit precision using a fixed-point parameter, then the coding efficiency is improved, but the weighting factor cannot be accurately represented when it falls outside the predefined range
Solution Approach 1:
The weighting factor representation is segmented into two parts: a fixed-point integer part and a fractional part. The integer part uses predetermined bit precision for efficient coding, while the fractional part extends the representable range. This segmentation allows the system to maintain coding efficiency for common cases while accommodating extreme values when needed.
Solution Approach 2:
The system dynamically adjusts the representation method based on the weighting factor value. When the weighting factor falls within the fixed-point representable range, it uses the efficient fixed-point format. When it exceeds this range, the system switches to an extended representation format, making the precision mechanism adaptive to different value ranges.
2Productivity
If the index for weighting factor is defined with predetermined bit precision, then the coding efficiency is improved, but there are cases where the weighting factor cannot be represented
Solution Approach 1:
The system changes the parameter representation format based on the weighting factor value. For most cases within the normal range, it uses the compact fixed-point index format for high coding efficiency. For exceptional cases where the weighting factor exceeds the fixed-point range, it switches to an extended format that can represent these out-of-range values, thus maintaining both efficiency and reliability.
3Productivity
If a fixed-point precision parameter is used to represent the weighting factor, then the coding efficiency is improved, but the precision is insufficient for extreme values
Solution Approach 1:
The weighting factor is segmented into an integer component and a fractional component. The integer component is encoded with fixed-point precision for efficiency, while the fractional component is handled separately to maintain precision for extreme values. This segmentation allows the system to optimize coding efficiency for the majority of cases while preserving precision when needed.
Data Source
AI summary
According to an embodiment, an encoding device includes a deriving unit and an encoding unit. The deriving unit is configured to derive a first reference value based on fixed point precision representing roughness of a weighting factor that is used for multiplying a reference image. The encoding unit is configured to encode a first difference value that is a difference value between the weighting factor and the first reference value and the fixed point precision. The weighting factor is included in a first range of predetermined bit precision having the first reference value at approximate center. The first difference value is in the predetermined range.