Multi-Algorithm Image Processing Chain Optimization for Efficient and Accurate Image Analysis

Abstract

In this paper, an algorithm is defined as an ordered set of processes or rules designed to achieve specific objectives. In the context of this study, an algorithm refers to the ordered set of computing processes used to enhance image processing. This research focuses on designing an algorithm for image processing, restricted to a new algorithm that employs cutting-edge techniques in both image processing and computing. The algorithms examined in this study will be limited to those suitable for real-time applications and high-resolution images. The study will compare algorithms, excluding others outside this scope. Performance metrics such as speed, efficiency, and reliability will be key parameters, considered without regard for cases beyond those specified during the algorithm's design. Genetic algorithms, differential evolution, and rank-based uniform crossover are the fundamental features of the two algorithms proposed for optimisation of image processing chains; specifically, LCHF, IPCO, and MIPCO.