Motion Vector Difference Coding With Cost-Based Bit Prediction
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in encoding and decoding motion vectors, particularly in predicting and signaling motion vector differences (MVD), which affects compression efficiency and decoding accuracy.
Innovation Solution
The proposed method involves processing circuitry that calculates cost values for various bit combinations of MVD, determines a combination of prediction values with the lowest cost, and decodes indicators to accurately predict MVD, using context models and template matching to enhance the decoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional motion vector coding methods are used, then the encoding process is simple, but the compression efficiency and decoding accuracy are insufficient
Solution Approach 1:
The patent performs preliminary actions by calculating cost values for multiple possible bit combinations before final decoding. The decoder computes template matching costs and smoothness costs for various MVD predictions in advance, then selects the optimal combination based on these pre-calculated metrics, improving accuracy without proportionally increasing complexity.
Solution Approach 2:
The patent replaces traditional mechanical bit-by-bit decoding with a cost-based selection mechanism. Instead of sequentially decoding each bit according to fixed syntax, the system evaluates multiple prediction combinations using template matching and smoothness criteria, then selects the optimal combination, substituting rigid mechanical decoding with flexible cost-optimal selection.
2Measurement precision
If more bits are used to code MVD, then the precision of motion vector representation improves, but the bitrate increases
Solution Approach 1:
The patent changes parameters by dynamically selecting which bits to predict and how many bits to explicitly code based on cost calculations. Instead of using a fixed number of bits for MVD coding, the system adapts the coding precision based on template matching results and smoothness metrics, achieving high precision when needed while reducing bitrate when predictions are accurate.
Solution Approach 2:
The patent implements feedback by using template matching costs and smoothness costs to guide the decoding process. The decoder evaluates multiple prediction hypotheses, compares them against reference data and smoothness criteria, and uses this feedback to select the optimal bit combination, ensuring high precision while minimizing the number of bits required.
3Productivity
If prediction methods are applied to MVD bits, then the computational complexity during decoding increases, but the compression efficiency improves
Solution Approach 1:
The patent applies partial action by selectively predicting only certain bits of the MVD codeword rather than all bits. The system identifies which bits benefit most from prediction based on template matching and smoothness analysis, applying prediction to those specific positions while using direct coding for others, thus improving compression efficiency without excessive computational overhead.
Solution Approach 2:
The patent applies local quality by using different coding strategies for different parts of the MVD representation. Certain bits are predicted using template matching and smoothness criteria, while other bits are coded directly. This localized application of prediction methods optimizes the balance between compression efficiency and computational complexity for each specific bit position.
Data Source
AI summary
Processing circuitry receives coded information of a motion vector difference (MVD). The processing circuitry calculates cost values associated with value combinations for a plurality of bits in coding bits of the MVD, at least one of the plurality of bits is a bit in a codeword for indicating a magnitude for the MVD. The processing circuitry determines a combination of prediction values for the plurality of bits from the value combinations, the combination of prediction values is associated with a lowest cost value in the cost values. The processing circuitry decodes the coded information of the MVD to obtain one or more indicators for the combination of prediction values, the one or more indicators indicates whether the plurality of bits is correctly predicted by the combination of prediction values. The processing circuitry determines the MVD based on the combination of prediction values and the one or more indicators.