Display Demura Compensation Data Compression via Down-Sampling
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Solution Overview
Problem
Display technologies face challenges in efficiently compressing and decompressing demura compensation data, leading to increased storage space and bandwidth requirements due to the large size of compensation data used to address brightness irregularities in display panels.
Innovation Solution
A system and method that involves down-sampling, quantifying, and converting compensation data into index data and code streams, reducing data size through lossy and lossless compression techniques, allowing for efficient storage and transmission while maintaining decompression accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If compensation data is stored in full resolution, then display quality is maintained, but storage space and bandwidth requirements increase significantly
Solution Approach 1:
The compensation data is segmented into multiple code streams through down-sampling and quantification processes. Each code stream represents a portion of the original data with reduced resolution, allowing selective reconstruction while maintaining overall display quality. This segmentation enables efficient storage by storing only essential data components.
Solution Approach 2:
The patent applies parameter changes by transforming the compensation data from full resolution to down-sampled and quantified representations. The data undergoes systematic reduction in precision parameters (down-sampling factor, quantization levels) to achieve compact storage while preserving sufficient quality for display compensation purposes.
2Quantity of substance
If compensation data is compressed through down-sampling and quantification, then storage space is reduced, but data precision is lost
Solution Approach 1:
The patent introduces intermediary code streams as mediators between the original compensation data and the final decompressed output. These code streams serve as intermediate representations that capture essential data characteristics at reduced precision, enabling efficient storage while allowing accurate reconstruction through the decompression process.
Solution Approach 2:
The down-sampling and quantification operations are performed as preliminary actions before storage, systematically reducing data precision in advance. This preliminary compression allows the system to store only the most critical data components, with the understanding that full precision will be restored through the decompression and reconstruction process.
3Productivity
If multiple code streams are generated from quantified data, then compression efficiency is improved, but processing complexity increases
Solution Approach 1:
The quantified compensation data is segmented into multiple code streams, each representing a specific portion or aspect of the original data. This segmentation improves compression efficiency by allowing independent processing and storage of each code stream, while the modular structure actually simplifies the overall processing architecture compared to handling a single large data block.
Solution Approach 2:
The patent transforms the data from a single-dimensional full-resolution representation into a multi-dimensional structure with multiple code streams at reduced resolution. This dimensional transformation enables more efficient compression by exploiting the reduced complexity in each dimension, while the structured organization of code streams facilitates systematic processing during decompression.
Data Source
AI summary
Embodiments of the present disclosure provide a system for display. The system includes a display having a plurality of pixels, a processor, and a control logic. The processor includes a graphics pipeline configured to generate a plurality of pieces of pixel data for the plurality of pixels and a pre-processing module configured to generate a plurality of pieces of compensation data for the pixel data and compress the compensation data. The compensation data is compressed by determining a plurality of pieces of quantified down-sampled compensation data based on the compensation data, converting the quantified down-sampled compensation data into M units of index data, and converting the M units of index data into M code streams. The control logic is operatively coupled to the display and the processor and includes a post-processing module configured to decompress the compressed compensation data based on the M code streams to provide control signals.