Reference Picture List Handling for Memory-Efficient Inter Prediction
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Solution Overview
Problem
Existing video compression technologies face challenges in efficiently processing next-generation video content with high-spatial resolution, high-frame rate, and high dimensionality, requiring improved prediction technologies to manage memory and processing resources effectively.
Innovation Solution
A method and device for constructing a reference picture list in video signals using inter prediction, involving the use of short-term and long-term reference pictures, with specific flags and modulo values to define entry types and optimize memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a reference picture list is constructed using traditional methods for high-resolution video, then prediction accuracy is improved, but memory requirements and processing complexity increase significantly
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 reference pictures differently based on their temporal characteristics, reducing memory complexity while maintaining prediction accuracy for high-resolution video content.
Solution Approach 2:
The patent introduces specific parameters to differentiate reference picture types: a flag indicating whether a reference picture is STRP or LTRP, and POC (picture order count) difference values. These parameter changes enable efficient classification and management of reference pictures, optimizing the balance between prediction accuracy and memory usage.
2Measurement precision
If the reference picture list includes more entries for high-frame rate video, then prediction precision improves, but the number of syntax elements and processing overhead increase
Solution Approach 1:
The patent extracts and separates the identification of reference picture types from the general reference picture list construction. By using flags and POC difference values to identify STRP and LTRP entries, the system can efficiently manage syntax elements and reduce processing overhead while maintaining comprehensive reference picture coverage for high-frame rate video.
3Reliability
If traditional reference picture management is used for high-spatial resolution video, then prediction capability is sufficient, but memory storage and access requirements become excessive
Solution Approach 1:
The reference picture management system is made dynamic by allowing flexible classification of reference pictures into STRP and LTRP categories. This dynamic approach enables the system to adaptively manage memory resources based on the temporal characteristics of reference pictures, maintaining prediction capability while reducing overall memory storage requirements for high-spatial resolution video.
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.