Hybrid Open-Loop Closed-Loop Video Compression Prediction
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Solution Overview
Problem
There is a tension between the small block sizes required for effective prediction in video compression and the large block sizes needed for efficient transform coding, particularly at higher resolutions, which affects prediction accuracy and noise growth.
Innovation Solution
A method of compression coding that combines a closed-loop predictor capable of exact reconstruction with an open-loop predictor, using a weighted sum of their outputs to control noise growth and optimize prediction accuracy, where the weighting factor varies with picture content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If small block sizes are used for effective prediction, then prediction accuracy is improved, but transform coding gain deteriorates
Solution Approach 1:
The patent combines two prediction approaches: closed-loop prediction (using reconstructed values from the decoder) and open-loop prediction (using original input values). This merging allows the system to benefit from both small block size prediction accuracy and large block size transform coding efficiency, resolving the contradiction between the two requirements
2Loss of energy
If large block sizes are used for efficient transform coding, then transform coding gain is improved, but prediction accuracy deteriorates
Solution Approach 1:
The patent applies different prediction strategies to different parts of the coding process. Closed-loop prediction is used where exact reconstruction is possible, while open-loop prediction is used where it is not, allowing each region to operate at its optimal block size for its specific function
3Adaptability or versatility
If open-loop prediction is used to improve prediction flexibility, then prediction capability is improved, but noise growth increases
Solution Approach 1:
The patent introduces a weighting parameter that controls the contribution of open-loop prediction to the overall prediction. By adjusting this parameter, the system can balance between the adaptability benefits of open-loop prediction and the noise growth drawbacks, optimizing performance for different picture content types
Data Source
AI summary
In a method of video coding, in which a difference is formed between input picture values and picture prediction values and that difference is transforming with a DCT, the picture prediction is formed as: P=(1−c)Pc+CPo where Pc is a closed loop predictor which is restricted to prediction values capable of exact reconstruction in a downstream decoder and Po is a spatial predictor which is not restricted to prediction values capable of exact reconstruction. The factor can vary from zero to unity depending on a variety of parameters.


