Motion Vector Prediction Lists with Selective Comparisons in Video Coding
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Solution Overview
Problem
Existing video codecs face challenges in accurately generating motion vector prediction lists due to redundant comparisons, leading to uncertainty and degradation in picture quality during decoding.
Innovation Solution
A method is introduced to reduce complexity by performing limited motion information comparisons between candidate pairs, utilizing a merge process to create a motion prediction candidate list that includes spatial and temporal motion predictions, and applying specific criteria to determine inclusion in the list.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion information comparisons are performed between all candidate pairs to generate motion vector prediction lists, then prediction accuracy is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the motion information comparison process by dividing candidate pairs into different groups based on their spatial and temporal relationships. Instead of comparing all candidates uniformly, the method performs targeted comparisons only for specific candidate pairs that are most likely to provide useful prediction information, thereby reducing overall computational complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent applies partial action by performing motion information comparisons only for a subset of candidate pairs rather than all possible pairs. The method selectively compares motion information based on predefined criteria such as spatial adjacency and temporal proximity, executing only the necessary comparisons that contribute most to prediction accuracy while avoiding redundant computations.
2Reliability
If redundant motion information comparisons are performed, then comprehensive prediction coverage is achieved, but processing time and computational resources are wasted
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and organizing candidate motion vectors into structured groups based on their spatial and temporal relationships before the actual comparison process. This preliminary organization allows the decoder to quickly determine which comparisons are necessary and which can be skipped, ensuring comprehensive prediction coverage without wasting time on redundant comparisons.
Solution Approach 2:
The patent implements self-service mechanisms where the motion vector prediction system automatically identifies and eliminates redundant candidate pairs based on predefined criteria. The decoder uses the structured organization of candidates to self-determine the minimal set of comparisons needed, eliminating the need for exhaustive comparisons while maintaining reliable prediction coverage.
3Measurement precision
If motion vector prediction lists are generated with multiple candidates, then prediction accuracy is improved, but the size of the prediction list and associated data transmission increase
Solution Approach 1:
The patent extracts only the most essential motion information from candidate vectors to form the prediction list. By selectively taking out key motion vectors that provide the most valuable prediction information and excluding redundant ones, the method maintains accurate prediction while minimizing the size of the prediction list and reducing data transmission requirements.
Data Source
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AI summary
The invention relates to a method for encoding, a method for decoding, an apparatus, computer program products, an encoder and a decoder for video information. The motion vector for a block in a video image is predicted from a set of motion vector prediction candidates determined based on previously-coded motion vectors. A motion vector prediction candidate is included in the set based on the location of the block associated with the first spatial motion vector prediction candidate and in comparison with motion vector prediction candidates already in the set.