Video Encoding Bit Allocation by Frame Complexity
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Solution Overview
Problem
The JVT-G012 bitrate control algorithm in H.264/AVC video coding does not consider encoding complexity at the frame level, leading to fluctuations in the peak signal-to-noise ratio (PSNR) curve and a decrease in the average PSNR of video sequences due to equal bit allocation among P-frames in a group of pictures.
Innovation Solution
A video encoding method that determines bit allocation based on the relative encoding complexity of frames within a group of pictures, reallocating bits from low-complexity frames to high-complexity frames to stabilize the PSNR curve and maintain an average encoding bitrate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If equal bit allocation is used among P-frames in a group of pictures, then the bit allocation process is simple, but the PSNR curve fluctuates and the average PSNR decreases
Solution Approach 1:
The patent applies local quality by differentiating bit allocation for different P-frames based on their encoding complexity. Instead of uniform allocation, the system identifies high-complexity P-frames (containing important visual information) and allocates more bits to them, while low-complexity P-frames receive fewer bits. This localized differentiation resolves the contradiction by improving PSNR quality through targeted resource allocation while maintaining reasonable operational simplicity through automated complexity detection.
Solution Approach 2:
The patent changes the bit allocation parameter dynamically based on encoding complexity assessment. By introducing a complexity metric and adjusting bit allocation accordingly, the system transforms from static equal allocation to dynamic adaptive allocation. This parameter change enables the system to maintain smooth PSNR curves by ensuring adequate bits for complex frames while accepting simpler frames use fewer bits, thus resolving the quality-fluctuation issue.
2Manufacturing precision
If bit allocation considers encoding complexity at frame level, then the average PSNR improves, but the bit allocation process becomes more complex
Solution Approach 1:
The patent implements self-service by enabling the encoding system to automatically assess its own encoding complexity for each P-frame and make autonomous bit allocation decisions. The system evaluates motion complexity, prediction accuracy, and visual importance metrics, then self-adjusts bit allocation without external intervention. This self-service mechanism resolves the complexity contradiction by embedding the assessment logic within the existing encoding pipeline, improving average PSNR while avoiding additional external control complexity.
Solution Approach 2:
The patent introduces feedback loops where encoding complexity metrics are continuously monitored and fed back to the bit allocation decision-making process. The system measures actual encoding outcomes (such as rate-distortion performance) and adjusts subsequent bit allocations based on this feedback. This feedback mechanism enables the system to achieve improved average PSNR by learning from past encoding experiences, while the automated feedback processing keeps the added complexity manageable through systematic rather than ad-hoc adjustments.
Data Source
AI summary
This application discloses a video encoding method and apparatus and an electronic device, and belongs to the field of communications technologies. The method includes: determining, based on a first ratio, a first bit number, and a first number, a second bit number for encoding a first picture; and encoding the first picture based on the second bit number, where the first ratio is a ratio of predicted encoding complexity of the first picture to actual encoding complexity of M frames of second pictures, the first picture is an unencoded first frame of picture in a target group of pictures, the M frames of second pictures are encoded pictures in the target group of pictures, the first bit number is the number of remaining bits in the target group of pictures, the first number is the number of unencoded pictures in the target group of pictures.