An Adaptive Color Night Vision Scheme Tuned Enhanced Particle Swarm Optimization

Abstract

Color night vision has been the debate of extensive research during the last ten years, primarily due to its impor¬tance in many real applications. In this research a brightness compensation system in vision images and videos based on Evolutionary Algorithms (EAs) was proffered. Enhanced Particle Swarm Optimization (EPSO) has been proved to be effective at finding optimal solutions of the proposed visioning problem by adapting the best global parameters of a novel extension to a local adaptive vision technique. As well the framework of the proposed system is being accurately developed and tested, and the mathematical analysis is mainly depends on the fitness score being developed, peak-signal-noise-ratio and the averaged brightness. Where the feasibility of the proposed system is compared with Differential Evolution (DE) and Artificial Neural Networks (ANNs). At all, the prototype of the system is envisaged to be applicable in many domains, and the avail of this systems leads to a so-called color night vision system.

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