Adaptive Loop Filter Coding With Exp-Golomb and Fixed-Length Signaling
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality image/video data, particularly in applications like virtual reality and augmented reality, leads to higher transmission and storage costs due to the increased amount of information, necessitating a more efficient compression technology and method for signaling adaptive loop filter information.
Innovation Solution
Implementing fixed order-based exponential Golomb coding for encoding/decoding filter coefficient information and using fixed length coding for binarization of adaptive loop filter (ALF) to enhance signaling efficiency and reduce coding complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If adaptive loop filter techniques are applied to improve compression efficiency and visual quality, then compression efficiency and visual quality are improved, but signaling complexity and coding overhead increase
Solution Approach 1:
The patent applies parameter changes by using exponential Golomb coding to efficiently represent filter coefficient values. This coding method transforms the representation of ALF parameters into a format that uses fewer bits for common values, thereby reducing signaling overhead while maintaining the ability to represent the full range of filter coefficients needed for high-quality compression
Solution Approach 2:
The patent employs fixed length coding for binarization of ALF information, which uses simple, fixed-bit representations instead of complex variable-length codes. This approach trades some precision for significantly reduced coding complexity and processing overhead, making the system more efficient overall
2Manufacturing precision
If filter coefficient information is encoded with high precision, then filtering quality is improved, but coding complexity and bitrate increase
Solution Approach 1:
The patent transforms filter coefficient values into exponential Golomb coded representations, which efficiently pack precision information into variable-length codes. Common filter coefficients that provide sufficient quality are represented with fewer bits, while less common values use more bits, achieving a balance between quality and complexity
Solution Approach 2:
The patent applies fixed length coding for binarization, which uses a standardized bit allocation that provides sufficient precision for most filtering operations without over-coding. This partial action approach applies full precision only where necessary while using reduced precision elsewhere, lowering overall coding complexity
Data Source
AI summary
According to the disclosure of the present document, information regarding ALF filter coefficients may be encoded/decoded by fixed order-based exponential golomb coding. In addition, information regarding a fixed filter in ALF may be binarized by fixed-length coding. Accordingly, signaling efficiency can be increased, and coding complexity can be decreased.