A comprehensive survey of visible and infrared imaging in complex environments: Principle, degradation and enhancement

Abstract

Images captured in extreme environments, including deep-earth, deep-sea, and deep-space exploration sites, often suffer from significant degradation due to complex visual factors, which adversely impact visual quality and complicate perceptual tasks. This survey systematically synthesizes recent advancements in visual perception and understanding within these challenging contexts. It focuses on the imaging principles and degradation mechanisms affecting both visible light and infrared images, as well as the image enhancement techniques developed to mitigate various degradation factors. The survey begins by examining key degradation mechanisms, such as low light, high water vapor, and heavy dust in visible light images (VLI), along with atmospheric radiation attenuation and turbulence distortion in infrared images (IRI). Next, a categorization and critical evaluation of both traditional and deep learning-based image enhancement algorithms is conducted, with a particular emphasis placed on their applications to VLI and IRI. Additionally, we summarize the application of image enhancement algorithms in complex environments, using deep underground scenes of coal mines as a case study, and analyze current trends by tracking the evolution of these algorithms. Finally, the survey highlights the challenges of image enhancement under complex and harsh conditions, offering a critical assessment of existing limitations and suggesting future research directions. By consolidating key insights and identifying emerging trends and challenges, this survey aims to serve as a comprehensive resource for researchers engaged in image enhancement techniques in extreme environmental conditions, such as those found in deep-earth, deep-sea, and deep-space environments.