.png){kind=icon}
.png){kind=icon}
Return
High-Linearity Remapping Scan With Genetic Algorithm for Digital Micro-Displays
.png){kind=icon}
OA
AI
DOI：10.1049/ell2.70619.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Highrefresh-rate digital micro-displays face a critical trade-off between data transmission efficiency and grayscale linearity. While fractal-based optimal scan achieves 100% transmission efficiency, it introduces severe grayscale non-linearity. This letter proposes a coupled error-guided remapping and GA-optimised weight-tuning scheme that restores grayscale linearity under fractal scan while preserving 100% transmission efficiency. For an 8-bit system, the proposed method improves the reconstructed-image PSNR to 40.54 dB with a 7.4% luminance loss, while reducing the residual sum of squares and maximum linearity error to 0.0219 and 3.3%, respectively. Both simulation and hardware demonstrations confirm the robustness of the proposed strategy for next-generation micro-displays.
Keywords:
CMOS digital integrated circuits
flat panel displays
fractals genetic algorithms
Image and Vision Processing and Display Technology
microdisplays
pulse width modulation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
0.8
Papers:
290
Citations:
1.2W