Video Encoding Lagrange Multiplier Optimization
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Solution Overview
Problem
Current video coding technologies, such as those using SSIM-based rate-distortion optimization, face inefficiencies due to inaccurate motion estimation and high bit rates, particularly when encoding residual signals, leading to suboptimal video compression efficiency.
Innovation Solution
A video processing method that calculates a Lagrange multiplier for each predict unit within a coding unit, using energy variances and scale factors to optimize encoding, thereby improving encoding efficiency by reducing inaccuracies in motion estimation and bit rate allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If SSIM-based rate-distortion optimization is used to improve subjective quality, then video quality is improved, but motion estimation accuracy deteriorates and bit rate increases
Solution Approach 1:
The patent applies local quality by calculating separate Lagrange multipliers for each predict unit based on local energy characteristics. The encoding device divides the current frame into multiple predict units and calculates energy for each predict unit and the current frame, then determines scale factors and Lagrange multipliers locally for each predict unit. This local optimization improves motion estimation accuracy while maintaining subjective quality.
2Productivity
If Lagrange multiplier is determined according to local feature of coding unit, then encoding efficiency is improved, but motion estimation accuracy deteriorates
Solution Approach 1:
The patent segments the coding unit into multiple predict units and calculates Lagrange multipliers for each predict unit separately. The encoding device calculates energy for each predict unit and the current frame, then determines scale factors and Lagrange multipliers for each predict unit based on local energy characteristics. This segmentation allows motion estimation to be performed with higher accuracy at the predict unit level while maintaining encoding efficiency.
3Productivity
If Lagrange multiplier is determined according to local feature of coding unit, then encoding efficiency is improved, but bit rate increases
Solution Approach 1:
The patent changes the parameter determination approach by calculating Lagrange multipliers based on energy characteristics of predict units rather than coding units. The encoding device calculates energy for each predict unit and the current frame, then determines scale factors and Lagrange multipliers locally for each predict unit. This parameter change optimizes the rate-distortion tradeoff at a finer granularity, improving encoding efficiency while controlling bit rate through more precise local optimization.
Data Source
AI summary
A video processing method includes: receiving video data, where the video data is divided into multiple frames; calculating a Lagrange multiplier of a current predict unit in a current coding unit, where the current predict unit is a segment of video signal within the current coding unit, the current coding unit is located in a current frame, and the current frame is one of the multiple frames; performing, by using the Lagrange multiplier of the current predict unit, encoding processing on the current predict unit according to a rate-distortion optimization algorithm to obtain an encoding result of the current predict unit; and sending the encoding result of the current predict unit to a decoder side. An encoding device and a decoding device respectively corresponding to the video processing method are also been provided.