I-Frame Size Estimation via Edge Strength Analysis
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Solution Overview
Problem
Existing video encoding systems face challenges in selecting optimal quantization parameters for I-frames, particularly due to reliance on previous frame characteristics, which can lead to estimation errors and buffer overflow/underflow issues, especially in real-time applications with scene changes and varying content complexity.
Innovation Solution
A video encoding system that selects quantization parameters based on a global edge strength value and available bitrate, independent of frame history, using a rate quantization model module that correlates frame size with global edge strength to maintain preferred compression quality within the allowed bitrate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If quantization parameters are selected based on previous frame characteristics, then encoding speed is improved, but estimation accuracy deteriorates due to scene changes and content complexity variations
Solution Approach 1:
The patent performs preliminary analysis of the current frame's characteristics (edge strength, complexity metrics) before encoding to predict the required bitrate and select appropriate quantization parameters. This preliminary action enables accurate parameter selection without relying on previous frames, resolving the contradiction by preparing necessary information in advance while maintaining encoding speed.
Solution Approach 2:
The patent implements a feedback mechanism where the actual bitrate and quality metrics from encoded frames are used to adjust and refine quantization parameter selection for subsequent frames. This closed-loop approach improves estimation accuracy over time while maintaining efficient encoding, addressing both speed and precision requirements.
2Reliability
If quantization parameters are selected to achieve preferred compression quality, then video quality is improved, but bitrate consumption increases causing buffer overflow
Solution Approach 1:
The patent dynamically adjusts quantization parameters based on frame-specific characteristics such as edge strength and content complexity. By changing parameters adaptively rather than using fixed values, the system achieves high video quality for complex frames while using lower bitrates for simpler frames, preventing buffer overflow while maintaining quality.
Solution Approach 2:
The patent introduces dynamic quantization parameter selection that adapts to the actual content of each frame. The system continuously monitors frame characteristics and adjusts parameters in real-time, enabling optimal balance between quality and bitrate consumption, thus preventing buffer overflow while maintaining preferred quality levels.
3Device complexity
If quantization parameters are selected from discrete values, then encoding complexity is reduced, but frame size control precision deteriorates
Solution Approach 1:
The patent selects quantization parameters from discrete available values but uses a refined selection process that evaluates multiple factors (edge strength, complexity, target bitrate) to choose the most appropriate discrete value. This partial action approach maintains the simplicity of discrete parameter selection while improving frame size control precision through intelligent selection among the discrete options.
Data Source
AI summary
Various embodiments of the present invention relate to systems, devices and method of video encoding that select a quantization parameter set based on a global edge strength value and an available bitrate for a corresponding compressed frame. Quantization parameters are selected using a mathematical correlation between the global edge strength value of the I-frame and an available bitrate/maxim target frame size for the corresponding compressed frame.