ABSTRACT

In image processing applications, we face the challenges of substantial computational requirements for calculating the objective function and requires considerably long optimisation time. In this paper, an operator named the pre-check operator (PCO) was proposed to reduce the whole optimization time. By integrating PCO with a standard genetic algorithm with elitist strategy (EGA), a new framework of pre-check genetic algorithm (PGA) was developed and compared with EGA based on a set of 10 benchmark instances with a known optimal solution. It was observed that PCO outperforms the results obtained using EGA.

中文翻译：

---

用于减少图像处理应用中算法优化时间的预检查算子

摘要

在图像处理应用中，我们面临着计算目标函数的大量计算需求的挑战，并且需要相当长的优化时间。在本文中，提出了一种称为预检查算子（PCO）的算子来减少整个优化时间。通过将 PCO 与标准遗传算法与精英策略 (EGA) 相结合，开发了一种新的预检查遗传算法 (PGA) 框架，并基于一组 10 个具有已知最优解的基准实例与 EGA 进行了比较。据观察，PCO 优于使用 EGA 获得的结果。