Video Encoding Control Using Quantization Statistics for Buffer Management
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Solution Overview
Problem
Conventional video encoding methods face challenges in maintaining image quality while preventing Coded Picture Buffer (CPB) underflow, with 1-pass encoding leading to significant deterioration and 2-pass encoding requiring high computational resources.
Innovation Solution
The proposed solution involves defining an 'encoding-order picture group' and 'quantization statistic' to selectively re-encode specific pictures within a group, increasing the CPB residual bit rate only when necessary, thereby reducing image quality deterioration and computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If 1-pass encoding is used to sequentially encode pictures, then encoding speed is improved, but image quality deteriorates significantly due to CPB underflow
Solution Approach 1:
The encoding process is segmented into multiple passes: a first pass that encodes all pictures to estimate complexity, and a second pass that uses these estimates to control bit rate allocation. This segmentation allows the system to achieve both fast initial encoding and high-quality final encoding without requiring all pictures to be encoded twice simultaneously.
Solution Approach 2:
The first encoding pass performs preliminary analysis of picture complexity and generates estimation information before the second pass. This preliminary action allows the second pass to make informed decisions about bit rate allocation and quantization parameters, preventing CPB underflow and maintaining image quality while preserving encoding efficiency.
2Manufacturing precision
If 2-pass encoding is used to encode all pictures twice, then image quality is improved by preventing CPB underflow, but computational load increases significantly
Solution Approach 1:
The second pass applies different encoding strategies to different pictures based on their estimated complexity. Simple pictures use higher quantization parameters (coarser encoding), while complex pictures use lower quantization parameters (finer encoding). This local quality approach maintains image quality where needed while reducing computational load on simple scenes.
Solution Approach 2:
Instead of uniformly encoding all pictures with high quality in the second pass, the system applies partial action by selectively adjusting encoding parameters only for pictures that require it based on complexity estimates. This avoids excessive computational effort on simple pictures while ensuring quality on complex ones.
3Manufacturing precision
If bit rate is increased for complex scenes to maintain image quality, then image quality is improved, but CPB underflow occurs in subsequent scenes
Solution Approach 1:
The system uses feedback from the first pass encoding results to adjust encoding parameters in the second pass. The complexity estimation information generated in the first pass serves as feedback that guides bit rate allocation decisions, allowing the encoder to prevent both image quality deterioration and CPB underflow by anticipating future encoding needs.
Solution Approach 2:
The first pass performs preliminary encoding of all pictures to generate complexity estimates before the actual quality-focused second pass. This preliminary action allows the system to plan bit rate allocation in advance, ensuring that complex scenes receive sufficient bit rate while simple scenes contribute to building up CPB reserves for future complex scenes.
Data Source
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AI summary
Video encoding is realized with small deterioration in image quality while suppressing underflow of a coded picture buffer (CPB) and with a smaller calculation amount than conventional 2-pass encoding. A video encoding control method which encodes an input video signal by controlling a generated bit rate so that a hypothetical buffer in a decoder does not fail includes: a step of sequentially encoding each picture in an encoding-order picture group in accordance with a predetermined encoding parameter, the encoding-order picture group including a predetermined number of pictures and being a collection of successive pictures in the order of encoding; a step of calculating a quantization statistic of each picture based on quantization parameter information used to encode each picture each time each picture is encoded, and checking whether or not the quantization statistic exceeds a predetermined threshold value, and a step of if the quantization statistic exceeds the predetermined threshold value, changing the encoding parameter so that the generated bit rate resulting from encoding is reduced and performing re-encoding from a first picture of an encoding-order picture group that is being encoded using the changed encoding parameter.