Macroblock Distortion Co-optimization via Pre-Encoder Analysis
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Solution Overview
Problem
Conventional rate/distortion optimization in video encoders assumes independent optimization decisions for current and future frames, leading to expensive exact co-optimization solutions, and lacks an inexpensive mechanism to account for future effects of current encoding decisions.
Innovation Solution
An apparatus with a pre-encoder module that analyzes frames to estimate distortion persistence and generates values representing these effects, which are used by a main encoder to modify the rate distortion cost expression and efficiently account for future frame impacts, implementable with a GPU-based encoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If exact co-optimization is performed to account for future frame effects, then video quality is improved, but computational complexity and encoding time increase significantly
Solution Approach 1:
The patent performs preliminary analysis of future frames to estimate distortion persistence before making encoding decisions for current frames. By pre-calculating the impact of potential distortions on future reconstruction quality, the encoder can make informed decisions without performing expensive exact co-optimization calculations during the main encoding process.
Solution Approach 2:
The patent uses inexpensive approximation methods (such as simplified distortion models and estimated weighting factors) instead of expensive exact optimization algorithms. These approximations provide sufficient quality improvement while keeping computational costs manageable, effectively using 'cheap' estimation techniques to achieve the desired quality enhancement.
2Productivity
If independent optimization decisions are made for each frame, then encoding speed is maintained, but future frame quality deteriorates due to unaccounted distortion persistence
Solution Approach 1:
The patent introduces feedback by analyzing how encoding decisions in current frames affect future frame reconstruction quality. The distortion persistence analysis provides feedback information that modifies the rate-distortion optimization criteria, allowing the encoder to make decisions that consider future quality impacts while maintaining encoding efficiency.
Solution Approach 2:
By performing preliminary distortion persistence analysis on future frames before making encoding decisions, the system prepares quality improvement information in advance. This allows independent frame-by-frame encoding to proceed at high speed while incorporating pre-computed quality considerations that prevent future quality deterioration.
3Manufacturing precision
If distortion persistence analysis is performed for future frames, then macroblock distortion co-optimization is improved, but encoding complexity increases
Solution Approach 1:
The patent applies distortion persistence analysis selectively to specific macroblocks and regions that are most likely to affect future frame quality. Rather than uniformly analyzing all macroblocks across all future frames, the system focuses computational resources on critical areas, achieving improved co-optimization while limiting the increase in encoding complexity.
Data Source
AI summary
An apparatus including a first module and a second module. The first module may be configured to generate one or more values based upon an analysis of one or more samples of a first frame. The second module may be configured to encode one or more samples of a second frame taking into account the one or more values generated by the first module. The one or more values generally represent a measure of an effect on the one or more samples of the first frame of encoding decisions made during encoding of the one or more samples of the second frame.