Underwater Image Enhancement Techniques – A Comprehensive Review

Abstract

Underwater image enhancement techniques seek to improve the visual quality and perceptual clarity of underwater images. Because of characteristics such as light attenuation, color distortion, scattering, and low contrast, underwater imaging presents unique challenges. As a result of these difficulties, image quality, visibility, and color accuracy suffer. Various strategies have been developed to address these concerns. Color correction, contrast enhancement, dehazing, noise reduction, and image restoration are all examples of underwater image enhancement techniques. Color correction methods seek to rectify color shifts caused by water absorption and scattering. By increasing the contrast between dark and bright regions, contrast enhancement techniques improve the visibility and crispness of underwater scenes. Dehazing techniques improve overall clarity by reducing the effects of light scattering. Noise reduction techniques suppress noise artifacts to improve visual detail and quality. Image restoration approaches address a variety of image degradation issues, including blurring, inpainting, and the restoration of missing or damaged regions. Statistical approaches, image processing algorithms, optimization methods, machine learning, and deep learning techniques can all be used to apply these concepts. The visual quality of underwater images can be considerably improved by using these underwater image enhancement techniques, resulting in higher visibility, restored colors, increased detail, and improved perception of underwater sceneries.