Image Encoding Motion Vector Candidate Selection
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Solution Overview
Problem
Conventional image encoding and decoding methods face complexity in calculating motion information for neighbor blocks, leading to inefficiencies in inter-prediction and intra-prediction processes, necessitating improved performance and efficiency.
Innovation Solution
An image encoding and decoding method that selects a motion vector candidate by determining the usability of neighbor blocks based on flags and prediction modes, and uses motion vector differences to derive motion information, optimizing prediction block generation and encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temporal prediction mode is used between pictures for motion information prediction, then prediction accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent dynamically adjusts the prediction approach by determining whether to use temporal prediction or intra-picture prediction based on block characteristics and motion activity. This dynamic selection optimizes the balance between prediction accuracy and computational complexity by adapting the prediction method to the specific content being encoded.
Solution Approach 2:
The patent changes the prediction parameters by using different reference blocks (spatial vs. temporal) and different prediction modes based on the characteristics of the current block. This allows the system to switch between high-accuracy temporal prediction and lower-complexity spatial prediction as needed.
2Productivity
If intra-prediction is made complicated to improve encoding performance, then image encoding performance is improved, but device complexity increases
Solution Approach 1:
The patent segments the prediction process into distinct modes (temporal prediction, spatial prediction, and their combinations) that can be independently selected and optimized. This segmentation allows complex prediction functionality to be achieved through modular, selectable components rather than a monolithic complex algorithm.
Solution Approach 2:
The patent applies partial action by selectively applying complex prediction methods only to blocks that benefit from them, while using simpler methods for other blocks. This is achieved through conditions that determine when to use temporal vs. spatial prediction based on motion characteristics and block content.
3Device complexity
If motion vector candidate selection is simplified, then device complexity is reduced, but prediction accuracy deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and organizing potential motion vector candidates from both spatial and temporal references before the actual prediction process. This preliminary organization allows for efficient selection of the best candidate without requiring complex real-time analysis during encoding.
Solution Approach 2:
The patent uses motion vector differences as an intermediary mechanism to bridge between simple candidate selection and accurate motion compensation. By encoding and transmitting only the difference between predicted and actual motion vectors, the system achieves high accuracy without requiring complex candidate evaluation.
Data Source
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AI summary
Disclosed are an image encoding and decoding method and an image decoding device for selecting a prediction candidate from reference blocks of a reference picture, which includes a current picture, and using the selected prediction candidate so as to derive motion information on a current block during image encoding and decoding. The image encoding and decoding method includes the steps of: configuring a spatial motion vector candidate; determining whether the reference picture of the current block is present within the current picture; and adding a spatial motion vector candidate in other block of the current picture encoded before the current block, when the reference picture of the current block is present within the current picture.