RGB-to-RGBG conversion algorithm with adaptive weighting factors based on edge detection and minimal square error.

Area of Science:

• Computer Vision
• Image Processing
• Display Technology

Background:

• RGBG panels have a different sub-pixel arrangement than standard RGB images.
• Existing RGB-to-RGBG conversion algorithms suffer from significant information loss and color fringing artifacts.

Purpose of the Study:

• To propose an improved RGB-to-RGBG conversion algorithm.
• To minimize information loss and color fringing artifacts during conversion.
• To enable accurate image display on RGBG panels.

Main Methods:

• Developed an Edge Detection and Minimal Square Error (EDMSE) algorithm.
• Utilized edge detection to differentiate image details prone to artifacts versus information loss.
• Applied adaptive weighting factors and a minimal square error mechanism for targeted processing.

Main Results:

• EDMSE slightly improved color fringing artifacts.
• Achieved 19.6% and 7% reduction in Mean Square Error (MSE) compared to direct assignment and weighting factor algorithms, respectively.
• Algorithm successfully implemented on a Field Programmable Gate Array (FPGA).

Conclusions:

• The EDMSE algorithm offers a superior method for RGB-to-RGBG image conversion.
• The approach effectively balances artifact reduction and information preservation.
• FPGA implementation facilitates practical application for RGBG panel image display.