Decoding Data Arrays With Missing Bit Adjustment
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Solution Overview
Problem
Existing data compression schemes, particularly lossy compression methods, face challenges in accurately decoding data values from encoded representations, leading to image quality degradation with each encoding/decoding cycle due to missing bits and interplay with decoding adjustments.
Innovation Solution
A method and decoder that select adjustment schemes based on patterns of missing bits to fill in missing data, applying different rounding modes to prevent image quality degradation, and using encoding hints to maintain consistent encoding parameters across cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression is applied to reduce data size, then bandwidth and storage requirements are reduced, but image quality degrades with each encoding/decoding cycle due to missing bits
Solution Approach 1:
The patent changes the parameter of bit representation by determining which bits are missing from the original data and applying targeted adjustments to those specific bit positions. This allows the system to maintain higher image quality by only modifying the necessary bits rather than applying blanket compression adjustments, thereby resolving the contradiction between reduced data size and maintained image quality.
2Productivity
If fixed-size data packets are used for compression, then bandwidth can be guaranteed, but data fidelity is lost due to discarded bits
Solution Approach 1:
The patent implements a feedback mechanism where the decoder determines which bits are missing from the compressed data and applies corrective adjustments based on this information. This feedback loop allows the system to recover data fidelity that would otherwise be permanently lost in fixed-size packet compression, while still maintaining the bandwidth efficiency benefits of fixed-size packets.
3Productivity
If multiple encoding/decoding cycles are performed, then data can be processed and transmitted, but image quality continuously degrades due to accumulating errors
Solution Approach 1:
The patent applies beforehand cushioning by identifying and correcting missing bits during the decoding process before they can propagate through subsequent encoding/decoding cycles. By proactively addressing the root cause of quality degradation (missing bits) rather than waiting for errors to accumulate, the system maintains stable image quality across multiple processing cycles while preserving processing throughput.
Data Source
AI summary
Disclosed herein is a method and apparatus for determining decoded data values for a data element of an array of data elements from an encoded representation of the array of data elements, wherein the decoding comprises determining which, if any, bits are missing for the data value(s) for the data element and selecting based on this an adjustment scheme to be applied for the data value(s) for the data element from a plurality of available adjustment schemes. Also disclosed are a method and apparatus for generating an encoding hint comprising an indication of the one or more encoding parameters that were used to generate the encoded representation which encoding hint can then be associated with the decoded data and then used when the decoded data is subsequently to be encoded.