Bit Rate Optimization via Spatial Temporal Complexity Analysis
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Solution Overview
Problem
Conventional streaming media technologies face challenges in balancing video compression and quality, as higher compression leads to increased distortion, making it difficult to choose a suitable bit rate that optimizes bandwidth while maintaining high-quality viewing experiences, especially under low internet bandwidth conditions.
Innovation Solution
A bit rate optimization system and method that analyzes spatial and temporal complexities of video frames using a vision evaluating formula to determine sensitivity to human eye, followed by standardization and application of a weight formula to automatically set an optimal bit rate for video compression, ensuring high-quality streaming even under low bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If higher compression is applied to media data for bandwidth optimization, then transmission bandwidth requirement is reduced, but media data quality deteriorates with higher distortion
Solution Approach 1:
The patent applies different compression levels to different regions of the video frame based on their importance. Important regions (such as areas with human faces, text, or key objects) are compressed less to maintain quality, while less important regions are compressed more aggressively. This is achieved through region-of-interest detection and adaptive bit rate allocation, allowing the system to optimize bandwidth usage without significantly degrading overall perceived quality.
Solution Approach 2:
The patent dynamically adjusts compression parameters such as bit rate, resolution, and frame rate based on network conditions, content characteristics, and device capabilities. By changing these parameters adaptively rather than using fixed compression settings, the system can maintain optimal quality for the given bandwidth constraints. The compression ratio is modified according to the importance of different video regions and the available transmission bandwidth.
2Loss of energy
If lower bit rate is used for video transmission, then bandwidth consumption is reduced, but video quality and viewing experience deteriorate
Solution Approach 1:
The system identifies and protects important visual regions by allocating more bits to these areas while using fewer bits for less important regions. This selective quality preservation ensures that key elements of the video content remain clear and recognizable even at lower overall bit rates, maintaining viewing experience quality while reducing bandwidth consumption.
Solution Approach 2:
The system performs pre-analysis of video content to identify important regions and objects before compression. By detecting regions of interest, human faces, text, and key objects in advance, the system can pre-allocate appropriate bit rates to these areas, ensuring that quality is preserved in critical regions while allowing more aggressive compression in non-critical areas.
3Device complexity
If uniform compression is applied to all video frames, then processing complexity is reduced, but quality inconsistency occurs across different scenes
Solution Approach 1:
The patent implements spatially adaptive compression where different compression ratios are applied to different regions within each frame based on their visual importance. This allows the system to maintain high quality in important regions while using lower compression in less important areas, achieving quality consistency across diverse video scenes without requiring overly complex processing.
Solution Approach 2:
The compression parameters are dynamically adjusted for each frame based on its specific characteristics, such as motion intensity, scene complexity, and presence of important objects. Rather than applying a static compression ratio to all frames, the system adapts the compression level frame-by-frame and region-by-region, maintaining quality consistency while managing processing complexity through efficient algorithms.
Data Source
AI summary
The present disclosure provides a bit rate optimization method that includes steps as follows. A video is provided. The spatial complexity and temporal complexity of the video are analyzed to evaluate the sensitivity of the human eye to serve as the basis for determining the bit rate of the video.