IMAGE ENHANCEMENT WITH THE APPLICATION OF LOCAL AND GLOBAL ENHANCEMENT METHODS FOR DARK IMAGES

Abstract

Image enhancement plays a crucial role in improving the visual quality and interpretability of images captured under poor illumination conditions. Dark images often suffer from low contrast, insufficient brightness, loss of details, and reduced visibility, which can negatively impact both human perception and computer vision applications. This paper presents an image enhancement framework that combines local and global enhancement methods to improve the quality of dark images. Global enhancement techniques are employed to adjust overall image brightness and contrast, ensuring balanced illumination across the entire image. Simultaneously, local enhancement methods focus on specific image regions to recover hidden details, preserve textures, and improve edge visibility. The integration of local and global enhancement approaches enables effective correction of illumination variations while maintaining natural image appearance. Experimental analysis demonstrates that the proposed method significantly improves image clarity, contrast, detail preservation, and visual perception compared to conventional enhancement techniques. The developed framework provides an efficient solution for enhancing dark images in applications such as surveillance, medical imaging, remote sensing, and digital photography.