Video Encoding Iteration Reference Frame Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional multimedia content encoding systems face challenges in achieving high-quality compression due to complex dependencies between signal portions, leading to suboptimal encoding and exponential complexity growth with the number of considered dependencies.
Innovation Solution
An iteration-based method for video encoding that involves encoding frames with a first set of parameters, analyzing and marking frequently used reference frames, and re-encoding using a second set of parameters, allowing for forward and backward iterations within a small sliding window to efficiently account for long-term dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional temporal linear encoding is used, then encoding complexity is manageable, but encoding quality is suboptimal due to inability to optimize reference frame allocation
Solution Approach 1:
The patent segments the encoding process into multiple iterative passes, where each pass focuses on optimizing specific reference frames independently. This allows the encoder to break down the complex global optimization problem into manageable local optimization tasks, improving encoding quality without requiring exponential complexity growth.
Solution Approach 2:
The patent performs preliminary encoding passes to identify and mark important reference frames before final encoding. By pre-identifying which frames require higher quality encoding based on their reference usage, the system can allocate bits more effectively in subsequent passes without needing to consider all possible dependencies simultaneously.
2Manufacturing precision
If joint optimization of multiple frames is attempted, then encoding quality improves, but complexity grows exponentially with the number of dependencies
Solution Approach 1:
The patent divides the set of frames to be optimized into smaller groups or individual frames that are optimized separately in different passes. This segmentation prevents the exponential complexity growth that would occur if all frames were optimized jointly, while still achieving quality improvements through multiple targeted optimization passes.
Solution Approach 2:
The patent performs partial optimization by focusing each encoding pass on specific reference frames rather than attempting to optimize all frames simultaneously. This partial action approach achieves sufficient quality improvement without the exponential complexity burden of complete joint optimization.
3Manufacturing precision
If more reference frames are considered in encoding, then encoding quality improves, but the sliding window size must increase
Solution Approach 1:
The patent segments the consideration of reference frames across multiple encoding passes rather than including all reference frames in a single large sliding window. Each pass operates with a manageable window size focused on specific reference frames, achieving the benefit of considering multiple references without requiring a large simultaneous window.
Solution Approach 2:
The patent performs preliminary analysis to identify which reference frames are most important before encoding. This allows the system to maintain a small sliding window during actual encoding while still effectively considering the impact of multiple reference frames through the preliminary identification and marking process.
Data Source
AI summary
A method for encoding video, comprising the steps of (A) encoding a number of frames of a video signal using a first sub-set of encoding parameters, (B) analyzing the encoded frames to find and mark reference frames that are used more than a predetermined number of times, and (C) re-encoding the video signal using a second sub-set of encoding parameters different than the first sub-set of encoding parameters when re-encoding the marked reference frames.