OLS DPB Parameter Management for Efficient Image Decoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to higher transmission and storage costs due to increased bit amounts, necessitating a more efficient image compression technique.
Innovation Solution
An image decoding method that involves deriving Decoded Picture Buffer (DPB) parameters for an Output Layer Set (OLS) and constructing a reference picture list for improved inter prediction, allowing adaptive updating of DPB parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image data is transmitted using conventional wired/wireless broadband line or stored using existing storage medium, then high-resolution and high-quality images can be transmitted/stored, but transmission cost and storage cost increase due to increased bit amount
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting DPB (Decoded Picture Buffer) parameters based on OLS (Output Layer Set) characteristics. The system changes buffering parameters adaptively to match the specific requirements of different output layers, thereby optimizing the balance between image quality and data量 for each layer without uniformly increasing overall bit amount.
Solution Approach 2:
The patent segments the image coding system into different Output Layers (OLS), each with its own DPB parameters. This segmentation allows independent optimization of buffering parameters for each layer, enabling high quality for important layers while reducing bit amount for less critical layers, thus resolving the contradiction between quality and data quantity.
2Productivity
If DPB parameters are not adaptively updated for different OLS, then the system structure remains simple, but coding efficiency is reduced
Solution Approach 1:
The patent implements preliminary action by pre-defining DPB parameter sets for different OLS types before actual coding operations. The system prepares and stores appropriate parameter configurations in advance, then selectively applies them during decoding based on the current OLS, thereby improving coding efficiency without introducing complex real-time parameter derivation logic.
Solution Approach 2:
The patent incorporates feedback mechanisms where the decoder receives OLS information from the bitstream and uses this feedback to select or derive the appropriate DPB parameters. This feedback loop enables adaptive parameter selection based on actual decoding requirements, improving coding efficiency while maintaining manageable complexity through standardized parameter derivation rules.
Data Source
AI summary
An image decoding method performed by a decoding device according to the present document comprises the steps of: obtaining image information including an output layer set (OLS) decoded picture buffer (DPB) parameter index for a target OLS and DPB parameter information; deriving DPB parameter information for the target OLS on the basis of the OLS DPB parameter index; performing a picture management process on pictures of a DPB on the basis of the DPB parameter information for the target OLS; configuring a reference picture list for a current picture on the basis of the pictures of the DPB; and performing an inter prediction on a block in the current picture on the basis of the reference picture list.