Reference Image List Reordering for Low-Bitrate Image Decoding
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Solution Overview
Problem
Existing image encoding and decoding technologies face challenges in achieving efficient compression at low bit rates, particularly in handling reference image lists and motion estimation for accurate prediction.
Innovation Solution
The proposed method involves modifying reference image lists by adding or removing specific types of reference images based on picture order count (POC)-related values and reordering them to enhance prediction decoding, using a hierarchical structure for image encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion estimation encoding is performed using reference images with different POC values, then prediction accuracy is improved, but device complexity increases due to managing multiple reference image lists
Solution Approach 1:
The patent dynamically adjusts the composition of reference image lists based on block group location and POC values. Different block groups use different reference image lists configured according to their temporal and spatial characteristics, allowing the system to adapt to varying prediction requirements without maintaining all possible reference configurations simultaneously
Solution Approach 2:
The patent divides the image sequence into multiple block groups and assigns different reference image list configurations to each block group based on their POC values and temporal relationships. This segmentation allows independent optimization of prediction parameters for different regions, improving overall prediction accuracy while managing complexity through localized configurations
2Productivity
If multiple reference image lists are maintained for different block groups, then compression efficiency is improved, but memory requirements and processing overhead increase
Solution Approach 1:
The patent creates reference image lists that serve multiple purposes: they function as prediction references for current block groups, as historical references for future block groups, and as sources for generating differential motion vectors. This multi-functionality reduces the need for separate dedicated reference structures, optimizing memory utilization while maintaining compression efficiency
Solution Approach 2:
The patent modifies reference image list parameters (composition, ordering, selection) based on POC values and block group characteristics rather than maintaining fixed reference structures. This dynamic parameter adjustment allows the same reference images to be reused in different configurations, reducing memory requirements while adapting to varying compression needs
3Measurement precision
If differential motion vectors are used for all blocks, then prediction accuracy is maintained, but bit rate increases due to signaling overhead
Solution Approach 1:
The patent applies different motion vector signaling strategies to different block groups based on their local characteristics and POC values. Some block groups use differential motion vectors relative to their reference images, while others may use direct motion vectors or simplified prediction methods, optimizing the balance between prediction accuracy and bit rate for each local region
Data Source
AI summary
An image decoding method may include: obtaining, from a sequence parameter set of a bitstream, information indicating a plurality of first reference image lists for an image sequence including a current image; obtaining, from a group header of the bitstream, an indicator for a current block group including a current block in the current image; obtaining a second reference image list by modifying a first reference image list indicated by the indicator, from among the plurality of first reference image lists, into the second reference image list; and prediction-decoding a lower block of the current block based on a second reference image included in the second reference image list.