Optical Flow Prediction Refinement for Subpicture Image Decoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to a significant increase in transmission and storage costs due to the increased amount of transmitted information, necessitating high-efficient image compression technologies.
Innovation Solution
An image encoding/decoding method that determines whether bi-directional optical flow (BDOF) or prediction refinement with optical flow (PROF) applies to a current block, fetching a prediction sample from a reference picture based on motion information, and deriving a refined prediction sample, with options for treating a current subpicture as a picture or within a larger picture context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality images are transmitted and stored, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent extracts and transmits only the essential image information by using efficient compression algorithms that identify and retain key visual features while discarding redundant data, thereby reducing the amount of transmitted information while preserving image quality
Solution Approach 2:
The patent employs advanced compression techniques that transform image data into a more compact representation by changing parameters such as color space, resolution levels, and frequency domain transformations, allowing high-quality images to be stored and transmitted with reduced bit rates
2Measurement precision
If image resolution and quality are increased, then visual fidelity is improved, but the amount of data to be transmitted increases
Solution Approach 1:
The patent creates compressed representations or proxies of high-resolution images that can be transmitted efficiently, using techniques such as progressive transmission where a low-resolution version is sent first followed by incremental refinement data, thereby maintaining transmission efficiency while supporting high-resolution output
3Productivity
If advanced compression techniques are applied, then transmission efficiency is improved, but encoding complexity increases
Solution Approach 1:
The patent implements dynamic encoding strategies that adapt compression parameters based on content characteristics, transmission conditions, and device capabilities, allowing the system to optimize between compression efficiency and computational complexity in real-time by adjusting encoding strength and algorithms according to the specific scenario
Data Source
AI summary
An image decoding method performed by an image decoding apparatus includes: determining that bi-directional optical flow (BDOF) or prediction refinement with optical flow (PROF) is applied to a current block; generating a prediction sample of the current block from a reference picture of the current block based on motion information of the current block; and deriving a refined prediction sample for the current block, by applying BDOF or PROF to the generated prediction sample of the current block, where the generating the prediction sample of the current block is performed based on whether a current subpicture including the current block is treated as a picture, where the generating the prediction sample of the current block comprises obtaining a reference sample specified by a position inside the reference picture and left-shifting a value of the reference sample, where the position inside the reference picture is clipped in a predetermined range.