Quantizer Offset Selection for Accurate Data Reconstruction
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Solution Overview
Problem
Existing data encoding and decoding methods suffer from errors due to quantization step size discrepancies between encoders and decoders, leading to inaccuracies in reconstructed data, particularly when using multiple quantizers with different offset values.
Innovation Solution
An apparatus and method that determine the optimal quantizer or de-quantizer by calculating errors between reconstructed and original data, using quantized coefficients from multiple quantizers with the same step sizes but different offset values, and combining scaling information to adjust step sizes, thereby generating a data stream that includes an indicator or offset information for accurate decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single quantizer with fixed offset value is used, then the encoding process is simple, but the reconstruction accuracy is limited due to quantization errors
Solution Approach 1:
The patent divides the quantization process into multiple parallel quantizers (first quantizer and second quantizer) with different offset values. Each quantizer processes the same input data independently, and the decoder selects the quantizer producing the smallest reconstruction error, thereby improving accuracy without requiring a single complex adaptive quantizer.
Solution Approach 2:
The patent changes the offset parameter of the quantizer to create multiple quantization versions. By using quantizers with different offset values (e.g., first offset and second offset), the system explores different quantization hypotheses and selects the optimal one based on reconstruction error, improving precision without increasing step size complexity.
2Measurement precision
If multiple quantizers with different offset values are used, then reconstruction accuracy improves, but the data transmission overhead increases due to additional indicator information
Solution Approach 1:
The patent extracts only the essential indicator information (quantizer selection indicator or offset value) from the multiple quantization results and transmits it separately. The actual quantized coefficient data remains unchanged, and only the minimal necessary information for reconstruction is added, reducing overhead compared to transmitting all quantizer parameters.
Solution Approach 2:
The patent introduces an indicator as an intermediary element that bridges the encoder and decoder. This indicator (selecting which quantizer was used or what offset value to apply) enables accurate reconstruction without requiring transmission of multiple complete quantizer configurations, efficiently mediating the information exchange.
3Productivity
If quantization step size is increased to reduce computational complexity, then processing speed improves, but quantization errors increase reducing accuracy
Solution Approach 1:
The patent applies partial action by using multiple quantizers with the same step size rather than one quantizer with a larger step size. This allows the system to maintain fine quantization granularity while still improving efficiency through parallel processing and error-based selection, avoiding the accuracy loss that would result from increasing step size.
Data Source
AI summary
The method for encoding data includes: receiving data; determining one quantizer from among a plurality of quantizers having a same quantization step size and different offset values; and transmitting an indicator and a quantized coefficient related to the determined quantizer. The method for decoding data includes: receiving an indicator and a quantized coefficient related to a quantizer; determining one de-quantizer from among a plurality of de-quantizers by using the indicator; and acquiring reconstructed data by de-quantizing the quantized coefficient by using the determined de-quantizer.