Introduction

Decision-making algorithms in outdoor environments face challenges in performance due to the suboptimal quality of input images. The quality of an image is characterized by various visible elements, including illumination, color, and gradients. Unfortunately, factors such as blur, noise, and block artifacts near edges can significantly impact these visible aspects, leading to a decline in the efficacy of computer vision-based decision-making algorithms. Consequently, leveraging artificial intelligence tools for image enhancement becomes crucial to enhance the robustness of these algorithms. This chapter provides an overview of the importance of image enhancement techniques and explores the factors influencing image quality, ultimately contributing to the subpar performance of vision-based applications.