Adaptive Frame Mapping for Parallel Video Compression
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Solution Overview
Problem
Current video compression methods that utilize parallel processing introduce significant performance loss, leading to inefficient compression and restoration of high-definition videos.
Innovation Solution
A video compression method that involves adaptive mapping based on differential features of image frames relative to reference frames, determining parallel processing conditions, and performing parallel compression analysis on image encoding units divided into hierarchical units to optimize encoding parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel compression processing is applied to video frames, then compression speed is improved, but compression performance loss increases
Solution Approach 1:
The video frame is divided into multiple independent regions (e.g., tiles, slices, or blocks) that can be processed in parallel. Each region is independently compressed using the same algorithm, enabling parallel processing while maintaining overall compression quality through consistent parameter application across all segments.
Solution Approach 2:
Compression parameters such as quantization levels, transformation types, or encoding settings are dynamically adjusted based on the specific characteristics of each video frame or region. This allows optimization of compression performance for diverse content while still benefiting from parallel processing capabilities.
2Ease of manufacture
If uniform compression processing is applied to all video frames, then processing simplicity is improved, but compression efficiency deteriorates
Solution Approach 1:
Different compression parameters and processing strategies are applied to different regions or frames based on their specific characteristics (e.g., motion intensity, detail content, importance). This allows optimization for each local region while maintaining a unified overall processing framework, balancing simplicity and efficiency.
Solution Approach 2:
The compression system dynamically adjusts processing parameters based on real-time analysis of video content characteristics. Frames or regions with high motion or detail receive different treatment compared to static areas, optimizing compression efficiency without requiring completely different processing pipelines.
Data Source
AI summary
A video compression method includes: acquiring a video to be compressed; determining encoding parameters respectively corresponding to a plurality of image frames in the video; and compressing the video based on the encoding parameters respectively corresponding to the plurality of image frames in the video. Determining encoding parameters respectively corresponding to a plurality of image frames in the video includes: for an image frame of a plurality of image frames: performing adaptive mapping on the image frame based on a differential feature of the image frame relative to a corresponding reference frame, to obtain a mapping result; determining a parallel processing condition corresponding to the image frame according to the mapping result; performing, in response to that a hierarchical feature of the image frame satisfies the parallel processing condition, parallel compression analysis on image encoding units in the image frame to obtain an encoding parameter for the image frame.