Research on super-resolution reconstruction for panoramic annular images

Panoramic annular image is an optical image that projects surrounding objects onto a circular area with the lens center as the focal point. It is widely used in petroleum pipeline monitoring system, but it is difficult to achieve high-quality images due to complex natural conditions in the surroundings, which affect the accuracy of pipeline monitoring system. To address this issue, we designed an optical image system which can obtain self-collected datasets. A dual-path network super-resolution algorithm is proposed, which utilizes an enhanced deep recursion network to extract detailed feature information from images, an attention mechanism network is utilized to extract important feature information from image in another path. Then the information of two paths is fused together to reconstruct high-resolution image. Experimental analysis and comparison were conducted on self-collected datasets using the algorithm, and the results demonstrated that our approach significantly improves image details and contributes to enhancing the accuracy of pipeline monitoring system.