Image Decoding with Adaptive Merge Candidates for Bi-Directional Prediction
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Solution Overview
Problem
Existing image coding methods using inter prediction are limited in coding efficiency due to restrictions on bi-directional prediction in the merging mode, leading to suboptimal compression performance.
Innovation Solution
An image coding method that determines a maximum number of merging candidates for each block, derives additional candidates for bi-directional prediction, and codes an index for the selected candidate, allowing for increased variety and flexibility in prediction directions and reference picture indexes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of merging candidates is limited to a fixed maximum number, then the device complexity is reduced and processing speed is improved, but the coding efficiency deteriorates due to insufficient prediction options
Solution Approach 1:
The patent applies dynamics by making the merging candidate list size adaptive rather than fixed. The list is dynamically adjusted based on the availability of bi-directional prediction candidates - when such candidates are available, the list includes them to improve coding efficiency; when not available, the list size is reduced to maintain processing speed. This dynamic adjustment resolves the contradiction between coding efficiency and processing complexity.
Solution Approach 2:
The patent changes the parameter of merging candidate list size based on prediction mode availability. By monitoring whether bi-directional prediction candidates exist and adjusting the maximum number of merging candidates accordingly, the system optimizes the balance between coding efficiency (more candidates) and processing complexity (fewer candidates).
2Productivity
If bi-directional prediction candidates are always included in the merging mode, then the coding efficiency is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent applies partial action by selectively including bi-directional prediction candidates in the merging mode based on their availability. Instead of always including them (excessive action), the system includes them only when they are actually available from neighboring blocks, achieving the coding efficiency benefit without the unnecessary processing complexity of always maintaining such candidates.
3Productivity
If the merging candidate list size is increased to provide more prediction options, then the coding efficiency is improved, but the processing time and complexity increase
Solution Approach 1:
The patent makes the merging candidate list size dynamic, adjusting it based on the actual availability of bi-directional prediction candidates. When such candidates are available, the list is expanded to improve coding efficiency; when not available, the list is kept smaller to reduce processing time. This dynamic sizing resolves the contradiction between coding efficiency and processing time.
Data Source
AI summary
An image coding method includes: determining a maximum number of merging candidates; deriving first merging candidates based on blocks spatially or temporally neighboring a current block; determining whether or not a total number of the first merging candidates is smaller than the maximum number; deriving, by making a combination out of the derived first merging candidates, a second merging candidate for bi-directional prediction when it is determined that the total number of the first merging candidates is smaller than the maximum number; selecting a merging candidate to be used for the coding of the current block from the first merging candidates and the second merging candidate; and coding, using the determined maximum number, an index for identifying the selected merging candidate, and attaching the coded index to the bitstream.