Inter Prediction Reference Picture Lists With Lower Memory Overhead
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Solution Overview
Problem
Existing video compression technologies face challenges in efficiently processing high-spatial resolution, high-frame rate video content due to increased memory storage and processing demands, particularly in constructing and managing reference picture lists for inter prediction.
Innovation Solution
A method and device for constructing a reference picture list by determining the type of reference pictures (short-term and long-term) based on picture order count differences and modulo values, optimizing the number of entries, and encoding necessary information to reduce syntax elements and improve memory management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the reference picture list includes both short-term and long-term reference pictures to improve prediction accuracy, then the prediction precision is improved, but the device complexity increases due to additional management overhead
Solution Approach 1:
The reference picture list is segmented into two distinct types: short-term reference pictures (STRP) and long-term reference pictures (LTRP). This segmentation allows the system to manage different reference pictures with different characteristics using separate mechanisms, reducing overall complexity while maintaining prediction precision.
Solution Approach 2:
Different reference pictures are assigned different qualities based on their temporal distance from the current picture. STRP use absolute POC difference for local temporal proximity, while LTRP use modulo POC for distant temporal references. This local quality differentiation optimizes prediction accuracy for each reference type without requiring a unified complex management system.
2Measurement precision
If the number of reference picture entries is increased to improve prediction accuracy, then the prediction precision is improved, but the memory storage requirements increase
Solution Approach 1:
The system changes the parameter used for identifying reference pictures based on their temporal characteristics. For STRP, absolute POC difference is used; for LTRP, modulo POC is used. This parameter change allows efficient identification and management of reference pictures, reducing memory requirements while maintaining prediction accuracy.
3Loss of information
If detailed syntax elements are used to fully describe reference picture list configurations, then the information completeness is improved, but the data complexity increases
Solution Approach 1:
The patent extracts and separates the essential information needed for reference picture list configuration into two distinct parts: STRP configuration (using absolute POC difference) and LTRP configuration (using modulo POC). This extraction reduces data complexity by removing redundant information while maintaining complete and accurate reference picture list descriptions.
Data Source
AI summary
Embodiments of the disclosure provide methods and devices for decoding video signals using inter prediction. According to an embodiment of the disclosure, a method for processing a video signal comprises constructing a reference picture list of a current picture in the video signal and performing a prediction for a current picture by using the reference picture list, wherein constructing the reference picture list comprising, if a first entry of the reference picture list corresponds to a short-term reference picture (STRP), obtaining a picture order count (POC) difference between a picture related to the first entry and another picture, and if a second entry of the reference picture list corresponds to a long-term reference picture (LTRP), obtaining a POC modulo value of a picture related to the second entry. A reference picture list for identifying a picture may be generated in a simplified and effective manner.