Survey of natural image enhancement techniques: Classification, evaluation, challenges, and perspectives

Abstract

Image enhancement is an essential technique used in many imaging applications. The main motivation of image enhancement is processing an image to be more suitable for specific utilization. Various image enhancement methods have been proposed in the existing literature. On the one hand, a variety of enhancement techniques make the classification more complex. On the other hand, the lack of image quality metrics specifically designed for enhanced images and the number of enhanced image quality databases as well as subjective data (ground truth) is limited, making the evaluation process difficult. This survey aims to guide the image enhancement research community to fill the above-mentioned gap and develop better and robust enhancement techniques. This survey 1) summarizes previous surveys of image enhancement techniques and existing classifications; 2) classifies the amount of techniques and analyzes their components, including how the performance has been evaluated; 3) surveys and recommends image quality metrics and databases that were designed for enhanced images; 4) discusses the challenges for image enhancement and its evaluation issues; and 5) proposes perspectives for the development of future image enhancement algorithms. This survey mainly focuses on image enhancement techniques that improve the perceived quality of natural images.