A Stereo‐Matching Technique for Recovering 3D Information from Underwater Inspection Imagery

Abstract

AbstractUnderwater inspections stand to gain from using stereo imaging systems to collect three‐dimensional measurements. Although many stereo‐matching algorithms have been devised to solve the correspondence problem, that is, find the same points in multiple images, these algorithms often perform poorly when applied to images of underwater scenes due to the poor visibility and the complex underwater light field. This article presents a new stereo‐matching algorithm, called PaLPaBEL (Pyramidal Loopy Propagated BELief) that is designed to operate on challenging imagery. At its core, PaLPaBEL is a semiglobal method based on a loopy belief propagation message passing algorithm applied on a Markov random field. A pyramidal scheme is adopted that enables wide disparity ranges and high‐resolution images to be handled efficiently. For performance evaluation, PaLPaBEL is applied to underwater stereo images captured under various visibility conditions in a laboratory setting, and to synthetic imagery created in a virtual underwater environment. The technique is also demonstrated on stereo images obtained from a real‐world inspection. The successful results indicate that PaLPaBEL is well suited for underwater application and has value as a tool for the cost‐effective inspection of marine structures.