Decoder-Aware Data Encoding for Variable Decoding Complexity
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Solution Overview
Problem
Current data encoding methods do not consider the dynamic state of decoders, leading to potential decoding performance degradation and compromised playback quality if the decoding resources are insufficient.
Innovation Solution
Encoding data based on knowledge of the target decoder's current, past, and predicted states, using customized encoding schemes that match the available decoding resources and complexity constraints to optimize decoding performance and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If encoding is performed without considering decoder state, then encoding simplicity is maintained, but decoding performance degrades when resources are insufficient
Solution Approach 1:
The encoder performs preliminary actions by determining the current state of the decoder before encoding data. The encoder selects an encoding scheme based on the decoder's available resources and complexity constraints, ensuring the encoded data can be successfully decoded without overwhelming the decoder's capabilities.
Solution Approach 2:
The encoding process becomes dynamic by adapting the encoding scheme based on the decoder's changing state. The encoder monitors decoder state (such as buffer fullness, processing load, and resource availability) and adjusts encoding parameters in real-time to match the decoder's current capabilities, rather than using a fixed encoding approach.
2Device complexity
If minimum decoder requirements are specified, then device complexity is reduced, but adaptability to different decoder capabilities is limited
Solution Approach 1:
The encoder changes encoding parameters dynamically based on the decoder's state and capabilities. By adjusting encoding complexity, bitrate, and other parameters according to the decoder's available resources, the system can adapt to a wide range of decoder capabilities without requiring complex minimum specifications or multiple encoding versions.
3Manufacturing precision
If encoding complexity is increased to improve quality, then data transfer rate decreases, but if encoding complexity is reduced, then decoding quality improves for resource-constrained decoders
Solution Approach 1:
The encoder dynamically changes encoding parameters such as complexity level, bitrate, and quality settings based on the decoder's state and resource availability. This allows the system to optimize the balance between data transfer rate and decoding quality in real-time, matching the encoder output to the decoder's processing capabilities.
Data Source
AI summary
Techniques for encoding data based at least in part upon an awareness of the decoding complexity of the encoded data and the ability of a target decoder to decode the encoded data are disclosed. In some embodiments, a set of data is encoded based at least in part upon a state of a target decoder to which the encoded set of data is to be provided. In some embodiments, a set of data is encoded based at least in part upon the states of multiple decoders to which the encoded set of data is to be provided.