Method of and System for Optimizing NURBS Surfaces for an Imaging System

Imaging systems play a critical role in various fields, including photography, surveillance, and scientific research. A non-uniform rational basis spline (NURBS) is a mathematical representation used in computer graphics for the modeling of 2D and 3D shapes. The clearer an image, the more detailed the data extracted from it; hence, optimizing the NURBS surfaces of imaging systems has been a persistent need. Previous methods lack an automatic and iterative way of enhancing the resolution of imaging systems by adjusting NURBS surfaces. The techniques available largely rely on manual adjustments with limited optimization objectives, making them time-consuming and potentially error-prone. Therefore, a method that can automatically optimize the imaging system with precision while reducing the requisite effort has been deeply needed.

Technology Description

This invention offers a process for augmenting NURBS optical surfaces in imaging systems. Using the principles of ray tracing, the method involves determining the number and location of field point sources and automatically increasing these until the image spot size variance is below a preset threshold. Likewise, the number of rays for each field point source is also iteratively increased until a set number of rays intersect each NURBS rectangular grid sub-area. What sets this technology apart is its automated approach to enhancing imaging resolution by the utilization of ray tracing techniques. Adjustments are made to the grid control points of each NURBS surface while maintaining symmetry or inviting freeform shapes, with the iterations driven by an optimization algorithm based on ray tracing. Iterations continue until image spot sizes meet set requirement or until improvement in spot size is below a predetermined value, implying a continuous strive towards achieving an optimal imaging system.