Image Inter-Prediction Candidate Lists for HD/UHD Decoding
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Solution Overview
Problem
Existing image encoding/decoding technologies face challenges in effectively determining and managing candidate lists for inter-prediction, particularly in high-definition and ultra-high-definition image processing, which affects image prediction performance and efficiency.
Innovation Solution
The method constructs candidate lists by adding candidates in a specific order, including spatially neighboring, temporally neighboring, and non-neighboring blocks, enhancing the prediction process through a structured approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a candidate list for inter-prediction is constructed using conventional methods, then the encoding/decoding process can proceed, but the prediction performance is insufficient for high-definition and ultra-high-definition images
Solution Approach 1:
The candidate list is segmented into multiple categories (spatial candidates, temporal candidates, combined candidates) with different construction methods. Each segment serves a specific prediction purpose, allowing the system to achieve high prediction performance for HD/UHD images while maintaining encoding efficiency through selective usage of different candidate types.
2Measurement precision
If various types of candidates are added to the candidate list to improve prediction accuracy, then the prediction performance improves, but the complexity of managing the candidate list increases
Solution Approach 1:
The candidate list construction is made dynamic through adaptive selection of candidate types and numbers based on block characteristics, picture type, and motion complexity. The system can flexibly adjust the composition of spatial, temporal, and combined candidates to optimize prediction accuracy while keeping management complexity manageable through context-based adaptation.
3Productivity
If a simple candidate list construction method is used, then the encoding/decoding process is fast, but the image compression efficiency is reduced
Solution Approach 1:
Candidate lists are constructed in advance during the encoding process with pre-organized spatial, temporal, and combined candidates. This preliminary construction allows the decoder to quickly retrieve and use appropriate candidates without performing complex searches, thereby maintaining high encoding/decoding speed while achieving improved compression efficiency through better prediction accuracy.
Data Source
AI summary
This disclosure provides an image encoding/decoding method and device and recording medium storing a bitstream. The image decoding method may comprise: constructing a candidate list related to prediction of a current block; generating a prediction block of the current block based on a candidate selected from the candidate list; and generating a reconstructed block of the current block based on the prediction block, wherein the constructing of the candidate list includes adding candidates to the candidate list in an order of a first candidate serving as a spatially neighboring block, a second candidate serving as a temporally neighboring block, and a third candidate serving as a non-neighboring block.