Display Device Error Correction via Bit Segmentation
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Solution Overview
Problem
Display devices, particularly in VR and AR systems, face challenges in maintaining image quality due to limitations in size, distance, and power, leading to visual artifacts and compromised user experience, as they struggle to precisely produce intended color values, resulting in errors that affect overall image quality and perceived color depth.
Innovation Solution
The implementation of an error correction process where the image processing unit determines errors at a pixel location and uses dithering techniques to adjust color values of nearby pixels, separating bits into subsets to compensate for color shifts in light emitters, generating output datasets that account for hardware limitations and color shifts, and feeding back error correction datasets to adjacent pixels to maintain image accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dithering is applied to compensate for color errors at pixel locations, then color accuracy is improved, but processing complexity increases
Solution Approach 1:
The color value processing is segmented into most significant bits (MSB) and least significant bits (LSB). The MSB processing compensates for light emitter color shifts, while LSB processing handles quantization errors. This segmentation allows targeted error correction without requiring complete reprocessing of all color data, thus improving color accuracy while managing processing complexity.
Solution Approach 2:
The system performs preliminary error calculation and compensation before final color output. By calculating the expected color output from light emitters and determining compensation values in advance, the system prepares correction data that is then applied during rendering. This preliminary action prevents error propagation and improves color accuracy without requiring complex real-time adjustments.
2Manufacturing precision
If error correction is performed for each pixel location, then image quality is improved, but processing time increases
Solution Approach 1:
The system merges error correction operations with the normal rendering pipeline. Instead of performing separate error correction passes, the compensation values are integrated into the color rendering process itself. The image processing unit simultaneously renders colors and calculates compensation, combining multiple functions into a unified operation that improves image quality without proportionally increasing processing time.
Solution Approach 2:
The rendering system performs its own error correction without requiring external intervention or additional specialized processing units. The image processing unit uses its existing resources to calculate compensation values and adjust color output. This self-service approach enables error correction while minimizing additional processing time overhead.
Data Source
AI summary
A display device has an image processing unit that determines an error for a pixel location that is based on the difference between an input color dataset and an output color dataset. The error is fed back to the image processing unit to propagate and spread across other neighboring pixel locations. In generating the output color values, the most significant bits (MSBs) and the least significant bits (LSBs) may be treated separately. The display device may extract the MSBs from the input and generate a first output color sub-dataset that is related to the MSBs. The display device may determine the LSBs from a difference between the input color dataset and the output MSBs. The display device may process the LSBs to compensate, adjust, scale, and quantize the values. The MSBs and LSBs may be re-combined to determine an actual color value displayed at the pixel location to determine the error.