HUD Image Distortion Correction via Parameter Optimization

The patent applies parameter changes by adjusting the distortion function parameters (α, β, γ) to correct multiple types of image distortion simultaneously. Instead of relying on the limited three-step method that only corrects plane distortion, this approach modifies the underlying distortion model parameters to achieve comprehensive correction including spatial distortion, image distortion, and brightness differences that the conventional method cannot address

The patent replaces the mechanical/manual correction system (cluster USM with movement and rotation) with a computational approach using distortion function parameter optimization. Instead of physically moving or rotating components to correct distortion, the system uses mathematical modeling and parameter adjustment (α, β, γ optimization through regression analysis) to achieve comprehensive distortion correction including types that manual adjustment cannot address

The patent merges the distortion correction functionality directly into the HUD system itself, eliminating the need for separate G-SCAN equipment. The distortion function parameter optimization is integrated into the existing HUD architecture, allowing the system to correct detailed image shape distortion using its own computational resources and existing components, thereby reducing device complexity while maintaining correction precision

The patent applies preliminary action by optimizing the distortion function parameters (α, β, γ) in advance through regression analysis using captured images and source data. This pre-optimization creates a corrected distortion model that compensates for source graphic distortion before the image is displayed to the driver. By establishing the optimal parameter set beforehand, the system corrects both the overall shape and the source graphic distortion simultaneously, rather than requiring separate correction steps