Underwater Imaging Using Low Rank Matrix and Sparse Representation for Oil Pipeline Inspection

Due to the critical importance of underwater pipeline integrity, particularly in the oil and gas transportation sector. This paper addresses the significance of applying low-rank matrix and sparse representation theories in the context of underwater imaging, with a primary focus on oil pipeline inspection. By comparing the effects of three algorithms on image processing, the superiority of the Structured Low-Dimensional Representation (SLDR) algorithm is demonstrated. The research aims to enhance the accuracy and quality of underwater images, ensuring the safety and integrity of subaqueous pipeline systems.