Video Stream Re-encoding Complexity Ratio Estimation
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Solution Overview
Problem
Current data coding systems for multimedia applications face inefficiencies in transcoding processes, particularly in regulating bit rates and predicting image complexities, leading to high costs and instability in transcoding systems.
Innovation Solution
A device and process for re-encoding image sequences that calculates a complexity ratio based on initial and re-encoded image complexities, updating an averaged complexity ratio to estimate the complexity of images to be re-encoded, allowing for more efficient bit rate regulation and reduced costs by minimizing intelligence requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If double pass coding techniques are used to accurately evaluate image complexities, then the prediction quality of complexities is improved, but the cost and complexity of the transcoding system increases significantly
Solution Approach 1:
The patent applies preliminary action by extracting complexity information before the actual re-encoding process. Specifically, the system extracts initial coding complexity (Xinit) from the incoming bit stream prior to re-encoding, and uses this pre-extracted information to predict the re-encoding complexity. This eliminates the need for expensive double pass coding while still achieving accurate complexity prediction, as the preliminary extraction of Xinit allows the system to forecast the required resources before committing to the full re-encoding operation.
Solution Approach 2:
The patent implements feedback by using the extracted initial complexity information to adjust and optimize the re-encoding process. The system feeds back the extracted Xinit value to guide the re-encoding operations, allowing dynamic adaptation of encoding parameters based on the actual content complexity. This feedback mechanism enables the system to achieve accurate complexity evaluation without requiring a separate second pass, thereby reducing overall system complexity while maintaining prediction quality.
2Adaptability or versatility
If complex re-encoding processes are applied to adapt bit rate to network constraints, then the adaptability to network requirements is improved, but the processing time and computational cost increases
Solution Approach 1:
The patent applies preliminary action by pre-extracting complexity information from the incoming bit stream before initiating the re-encoding process. This preliminary extraction of initial coding complexity (Xinit) allows the system to quickly assess the content characteristics and determine appropriate re-encoding parameters without requiring extensive processing time during the actual adaptation phase. By having this information ready in advance, the system can rapidly adapt to network constraints while minimizing computational overhead.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting re-encoding parameters based on the extracted complexity information and network constraints. The system changes encoding parameters such as quantization step size, bit rate allocation, and compression level according to the predicted complexity (Xpred) and current network conditions. This flexible parameter adaptation enables the system to optimize the balance between adaptability to network requirements and processing efficiency, avoiding unnecessary computational operations while maintaining optimal performance.
Data Source
AI summary
Image sequences are advantageously recoded based on an evaluation of complexities before and after trans-coding of the images. Initially, information is extracted representing at least the complexity of recoding each image. A complexity ratio is calculated in accordance with the complexities of images recoded previously using the aforementioned mode to the complexities of the initial coding of said images. After smoothing the complexity ratio undergoes updating. Each image is recoded according to the mode by estimating the complexity of each image to be recoded as the product of the complexity of the initial coding of the image by the smoothed complexity ratio for the mode.