Adaptive Search Range Management in Video Coding
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Solution Overview
Problem
Current video coding technologies face inefficiencies in managing search memory, leading to suboptimal coding performance due to fixed search range sizes and locations, which can result in increased hardware overhead and coding latency.
Innovation Solution
The proposed solution involves adaptive search range size and location management, where the search range size and location are determined based on the quantity and type of reference pictures, with larger ranges allocated to more frequently used reference pictures and smaller ranges for less frequently used ones, and the use of ordered lists to prioritize reference pictures for inter-picture prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed search range sizes and locations are used for all reference pictures, then hardware implementation is simplified, but coding efficiency deteriorates due to inability to adapt to different reference picture usage frequencies
Solution Approach 1:
The patent applies dynamics by making the search range size adaptive rather than fixed. The search range size is dynamically adjusted based on the quantity of reference pictures and their usage frequency. When more reference pictures are available, the search range is reduced; when fewer reference pictures are available, the search range is expanded. This dynamic adaptation resolves the contradiction by allowing the system to maintain simple hardware implementation while achieving high coding efficiency through context-dependent parameter adjustment.
Solution Approach 2:
The patent changes the search range size parameter based on the number of reference pictures. Specifically, the search range size is determined as a function of the quantity of reference pictures, allowing the system to optimize coding efficiency without changing the fundamental hardware architecture. This parameter change enables the system to adapt to different coding scenarios while maintaining hardware simplicity.
2Productivity
If larger search ranges are used for all reference pictures to ensure better reference block matching, then coding gain is improved, but hardware overhead and latency increase
Solution Approach 1:
The patent applies local quality by allocating different search range sizes to different reference pictures based on their individual usage frequencies and importance. Rather than using a uniformly large search range for all reference pictures, the system assigns larger search ranges only to reference pictures that benefit most from extensive searching, while using smaller search ranges for less critical reference pictures. This resolves the contradiction by concentrating hardware resources where they provide the most coding gain while reducing overhead elsewhere.
Solution Approach 2:
The patent uses partial action by applying large search ranges only when necessary (i.e., when the number of reference pictures is small or when specific reference pictures are highly important), rather than always using maximum search ranges. This selective approach ensures coding gain is achieved only when needed, while reducing hardware overhead in scenarios where smaller search ranges suffice.
3Device complexity
If uniform search range allocation is used for all reference pictures, then hardware resource management is simplified, but coding performance deteriorates due to inefficient memory usage
Solution Approach 1:
The patent changes the search range size parameter dynamically based on the quantity of reference pictures. The relationship between the number of reference pictures and the search range size is defined by a specific function or lookup table, allowing the system to automatically adjust memory allocation without complex manual management. This resolves the contradiction by providing adaptive memory management that improves coding performance while maintaining relatively simple hardware control logic.
Data Source
AI summary
Various schemes for managing search memory are described, which are beneficial in achieving enhanced coding gain, low latency, and/or reduced hardware for a video encoder or decoder. In processing a current block of a current picture, an apparatus determines a quantity of a plurality of reference pictures of the current picture. The apparatus subsequently determines, for at least one of the reference pictures, a corresponding search range size based on the quantity. The apparatus then determines, based on the search range size and a location of the current block, a search range of the reference picture, based on which the apparatus encodes or decodes the current block.