Structural Crack Image Enhancement: A Review of Techniques for Varied Environmental Conditions

Abstract

Structural health monitoring is crucial for ensuring the safe operation of civil engineering infrastructure. With the deep integration of computer vision technology and traditional inspection methods, along with the rapid advancement of smart maintenance concepts, image enhancement and quality improvement techniques for crack images captured in complex environments-such as above water, underwater, and in tunnels-have become increasingly important. These images often suffer from issues like blurriness, low contrast, and significant noise interference. By systematically reviewing spatial domain enhancement, frequency domain enhancement, and emerging deep learning-based methods, the core enhancement mechanisms and applicable scenarios of these approaches can be clarified, thereby providing a solid theoretical and technical foundation for intelligent crack identification and automated detection in complex environments in the future.