3D Data Decoding Arithmetic Context Modeling
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Solution Overview
Problem
The existing 3D data encoding schemes, such as those described in NPL 1, face inefficiencies in encoding and decoding mesh displacements and mesh motion information due to dependencies on syntax elements and contexts, leading to poor encoding efficiency.
Innovation Solution
A 3D data encoding and decoding apparatus that utilizes an arithmetic encoder and decoder to encode and decode mesh displacements by using a context to decode a part of the beginning of a prefix of a remainder of an absolute value of a coefficient, improving encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If arithmetic encoding scheme is used for mesh displacements and mesh motion information, then encoding capability is provided, but encoding efficiency is poor due to dependency on syntax elements and contexts
Solution Approach 1:
The patent changes the parameter of context modeling in arithmetic encoding by introducing a new context `ctxCoeffRemPrefix` that specifically models the prefix of the remainder of absolute coefficient values. This parameter change allows the encoder to capture statistical patterns in mesh displacement data more effectively, improving encoding efficiency without compromising reliability.
Solution Approach 2:
The patent segments the encoding process into distinct components: encoding the prefix of the remainder using context `ctxCoeffRemPrefix`, and handling the suffix separately. This segmentation allows each part to be optimized independently, with the prefix benefiting from context-based probability modeling and the suffix handled through standard arithmetic encoding, thereby improving overall encoding efficiency.
2Productivity
If context-based arithmetic encoding is used, then encoding efficiency improves, but device complexity increases due to context management requirements
Solution Approach 1:
The patent applies local quality by creating a dedicated context `ctxCoeffRemPrefix` specifically for modeling the prefix of remainder values, rather than using a single generic context for all encoding operations. This localized context modeling improves encoding efficiency for this specific component while keeping the overall system manageable by focusing complexity only where needed.
Solution Approach 2:
The context `ctxCoeffRemPrefix` serves multiple functions: it models the statistical distribution of prefix values, enables efficient encoding of mesh displacements, and can be applied to similar encoding scenarios. This multi-functionality justifies the added complexity by providing benefits across multiple encoding operations.
Data Source
AI summary
A 3D data decoding apparatus for decoding encoded data includes an arithmetic decoder configured to arithmetically decode a mesh displacement from the encoded data. The arithmetic decoder decodes a part of a beginning of a prefix of a remainder of an absolute value of a coefficient of the mesh displacement by using a context.