Neighboring Sub-Block Motion Modeling in Image Decoding
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Solution Overview
Problem
Existing image encoding and decoding technologies face challenges in effectively handling high-resolution or high-quality image content, particularly in predicting current blocks using neighboring block information, leading to inefficiencies in data compression and decoding processes.
Innovation Solution
The method involves identifying neighboring sub-blocks with the same motion vector, determining a representative motion vector and location information, and using these to predict the current block, thereby optimizing the prediction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neighboring block information is used to predict current blocks, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The current block is divided into multiple sub-blocks, and prediction is performed independently for each sub-block using neighboring sub-block information. This segmentation allows the use of detailed local information to improve prediction accuracy while managing computational complexity through localized processing rather than global analysis.
Solution Approach 2:
Different prediction parameters are determined for different sub-blocks based on their specific neighboring block configurations. Each sub-block uses locally adapted prediction models that consider the specific motion vectors and characteristics of its adjacent sub-blocks, improving overall prediction accuracy through localized optimization.
2Measurement precision
If sub-block level prediction is performed, then prediction precision is improved, but processing time increases
Solution Approach 1:
The block is segmented into sub-blocks that can be processed in parallel. By dividing the prediction task into independent sub-block operations, the method achieves higher prediction precision through fine-grained analysis while enabling parallel processing to mitigate the increase in total processing time.
Solution Approach 2:
Motion vectors and prediction parameters are pre-determined for neighboring sub-blocks before current block prediction. This preliminary preparation of reference data allows faster computation during the actual prediction phase, reducing the time penalty associated with increased prediction precision.
3Measurement precision
If motion vector information from multiple neighboring blocks is used, then prediction accuracy is improved, but data transmission requirements increase
Solution Approach 1:
Only the essential motion vector information from neighboring blocks is extracted and utilized for prediction, rather than transmitting all possible block data. This selective extraction maintains prediction accuracy by focusing on the most relevant motion parameters while significantly reducing the quantity of data that needs to be transmitted and processed.
Data Source
AI summary
Provided are an image decoding method and apparatus. The image decoding method includes identifying at least two neighboring sub-blocks that have a same motion vector and are adjacent to each other from among a plurality of neighboring sub-blocks adjacent to a current block, determining a representative motion vector and representative location information corresponding to the at least two neighboring sub-blocks, determining a parameter of a model for determining a motion vector based on the representative motion vector and the representative location information, determining a motion vector of a current sub-block included in the current block, based on location information of the current sub-block and the parameter, and predicting the current block based on the motion vector of the current sub-block wherein the representative motion vector is determined based on the same motion vector, and the representative location information indicates coordinates that are determined based on the at least two neighboring sub-blocks.