Video Encoding Adapted to Decoder Complexity
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Solution Overview
Problem
Existing data encoding methods do not consider the dynamic state of decoders, leading to potential degradation in decoding performance 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 take into account the decoder's available resources and complexity constraints to optimize decoding performance and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If encoding schemes are selected without consideration of decoder state, then encoding flexibility and speed are improved, but decoding performance and playback quality deteriorate when decoder resources are insufficient
Solution Approach 1:
The encoder performs preliminary actions by determining the current state of the decoder (buffer occupancy, processing speed) before encoding each frame. This allows the encoder to proactively adjust encoding parameters to match decoder capabilities, preventing buffer underflow/overflow and ensuring smooth playback without real-time feedback loops
Solution Approach 2:
The encoding scheme is made dynamic by continuously adapting encoding parameters (quantization, resolution, compression ratio) based on the decoder's current state. The encoder transitions between different encoding modes depending on decoder buffer levels and processing speed, optimizing both encoding efficiency and decoding performance in real-time
2Adaptability or versatility
If minimum decoder requirements are specified, then system compatibility is improved, but adaptability to different decoder capabilities deteriorates
Solution Approach 1:
The patent applies local quality by tailoring the encoding quality and complexity to match the specific capabilities of different decoder segments. High-end decoders receive higher quality encoding with more complex features, while lower-end decoders receive optimized encoding that matches their processing capabilities, ensuring each decoder operates at its optimal performance level without unnecessary complexity
Data Source
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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.