Lossless Video Compression via Adaptive Prediction Segmentation
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Solution Overview
Problem
Conventional video data compression methods either result in low compression ratios or high computational complexity, and lossy compression degrades video quality, leading to increased bandwidth burden and power consumption.
Innovation Solution
A method and device for lossless video data compression that divides video frames into compression regions and uses adaptive prediction modes based on statistical analysis to optimize prediction processing and entropy coding, reducing bandwidth requirements and improving data throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional lossless compression methods are used, then video quality is maintained, but compression ratio is low
Solution Approach 1:
The video frame is divided into multiple compression regions, and each compression region is further divided into multiple compression units. This segmentation allows different prediction modes to be applied to different regions, improving compression efficiency while maintaining video quality.
Solution Approach 2:
The patent uses adaptive prediction mode selection where the prediction mode parameter set is dynamically determined based on statistical analysis of optimal prediction modes from previously processed compression units. This dynamic adaptation improves compression ratio without compromising video quality.
2Manufacturing precision
If conventional lossless compression methods are used, then video quality is maintained, but computational complexity is high
Solution Approach 1:
The patent performs preliminary statistical analysis to determine the optimal prediction mode for each compression unit before actual compression. This preliminary action identifies the most effective prediction modes in advance, reducing the computational burden during the actual compression process while maintaining video quality.
Solution Approach 2:
The patent changes the parameter set of prediction modes adaptively based on the statistical results from previously processed compression units. By dynamically adjusting which prediction modes are used, the system reduces computational complexity while maintaining the video quality required for lossless compression.
3Quantity of substance
If lossy compression is used to increase compression ratio, then bandwidth burden is reduced, but video quality is degraded
Solution Approach 1:
The system uses entropy coding processing that adapts to the statistical properties of the prediction residuals, achieving efficient compression without quality loss. The entropy coder automatically adjusts its parameters based on the data characteristics, providing high compression ratios while maintaining lossless video quality.
4Productivity
If adaptive prediction mode selection is performed for each compression unit, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The statistical analysis to determine optimal prediction modes is performed in advance during the processing of each compression unit, and these results are stored for use in subsequent compression regions. This preliminary action avoids redundant calculations and reduces processing time while maintaining compression efficiency.
Solution Approach 2:
The determined optimal prediction mode parameter set is reused across multiple compression regions and subsequent video frames. This universal application of the determined parameters reduces processing time for each individual region while maintaining overall compression efficiency throughout the video sequence.
Data Source
AI summary
A method for lossless compression of video data is provided. The method includes; receiving video data including a plurality of video frames; dividing each of the plurality of video frames into a plurality of compression regions, wherein each compression region includes at least one compression unit; processing each compression region of a first video frame by: providing a prediction mode parameter set including a plurality of prediction modes; performing prediction processing on at least a part of the compression units using the prediction modes, and determining usage of the prediction modes; and selecting at least a part of the prediction modes as a preferred prediction mode parameter set based on the usage; performing prediction processing on subsequent video frames using the determined preferred prediction parameter mode set to obtain coding blocks; and performing entropy coding processing on the coding blocks to obtain compressed video data.