Probabilistic Bit-Rate Estimation for Video Coding
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Solution Overview
Problem
Existing video encoding technologies face challenges in reducing computational complexity for bit-rate and rate-distortion cost estimation, particularly in real-time, low-power applications such as cellular telephones and video cameras, where determining accurate bit-rates is computationally complex and not suitable for real-time processing.
Innovation Solution
A method that computes spatial variance for video data in a block, estimates a first bit-rate based on spatial variance and empirically determined transform coefficient thresholds, and variance multiplicative factors, to encode the block efficiently, thereby reducing computational complexity while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If actual coding of macroblock in all modes is performed to determine bit-rate, then bit-rate determination accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent uses a simplified, low-cost bit-rate estimation model that provides sufficient accuracy for mode selection without requiring full actual coding of all modes. This disposable estimation approach replaces the computationally expensive exact measurement, achieving acceptable precision at much lower computational cost.
Solution Approach 2:
The patent changes the parameter from exact bit-rate measurement to estimated bit-rate based on spatial information and statistical models. By transforming the measurement parameter from actual coding results to predicted values based on video content characteristics, the computational complexity is dramatically reduced while maintaining sufficient accuracy for practical mode selection.
2Measurement precision
If transform and quantization are performed to count non-zero coefficients for bit-rate estimation, then bit-rate estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent extracts only the essential spatial information features from the macroblock that are most strongly correlated with bit-rate, rather than performing the complete transform and quantization process. By taking out only the critical spatial statistics needed for estimation, the method achieves good bit-rate prediction without the full computational burden of transform coding.
Solution Approach 2:
Instead of performing the complete transform and quantization sequence, the patent applies partial action by computing only the necessary spatial variance and statistical moments. This partial computation provides sufficient bit-rate estimation accuracy for mode selection while avoiding the excessive computational cost of full transform processing.
3Device complexity
If spatial information curve fitting is used for bit-rate estimation, then computational complexity is reduced, but generalization ability deteriorates
Solution Approach 1:
The patent develops a universal bit-rate estimation model based on spatial information statistics that works across different video content types and coding conditions. By formulating a general statistical relationship that captures the essential correlation between spatial variance and bit-rate, the model achieves both low computational complexity and good generalization ability across diverse video sequences.
Data Source
AI summary
A method of video encoding is provided that includes computing spatial variance for video data in a block of a video sequence, estimating a first bit-rate based on the spatial variance, a transform coefficient threshold, and variance multiplicative factors empirically determined for first transform coefficients, and encoding the block based on the first bit-rate.