Subsea pipeline corrosion estimation by restoring and enhancing degraded underwater images

Subsea pipeline corrosion is considered as a severe problem in offshore oil and gas industry. It directly affects the integrity of the pipeline which further leads to cracks and leakages. At present, subsea visual inspection and monitoring is performed by trained human divers; however, offshore infrastructures are moving from shallow to deep waters due to exhaustion of fossil fuels. Therefore, inhospitable underwater environmental conditions for human diver demand imaging-based robotic solution as an alternate for visual inspection and monitoring of subsea pipelines. However, an unfriendly medium is a challenge for underwater imaging-based inspection and monitoring activities due to absorption and scattering of light that further leads to blur, color attenuation, and low contrast. This paper presents a new method for subsea pipeline corrosion estimation by using color information of corroded pipe. As precursor steps, an image restoration and enhancement algorithm are developed for degraded underwater images. The developed algorithm minimizes blurring effects and enhances color and contrast of the images. The enhanced colors in the imaging data help in corrosion estimation process. The image restoration and enhancement algorithm are tested on both experimentally collected as well as publicly available hazy underwater images. A reasonable accuracy is achieved in corrosion estimation that helped to distinguish between corroded and non-corroded surface areas of corroded pipes. The qualitative and quantitative analyses show promising results that encourage to integrate the proposed method into a robotic system that can be used for real-time underwater pipeline corrosion inspection activity.