Pipeline image haze removal system using dark channel prior on cloud processing platform. (4th May 2020)

• Record Type: Journal Article
• Authors: Li, Ce; He, Tan; Wang, Yingheng; Zhang, Liguo; Liu, Ruili; Zheng, Jing
• Is Part Of: International journal of computational science and engineering. Volume 22:Number 1(2020)
• Page Start: 84
• Page End: 95
• Publication Date: 2020-05-04
• Subjects: pipeline image processing -- dark channel prior -- atmospheric optical -- data access control; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

Abstract

Pipeline fault detection is very important application of pipeline robots for the security of underground drainage pipeline facilities. The detection performance of existing systems is closely related to the image definition in the complex pipeline environment in terms of darkness, water fog, haze, etc. In this paper, the techniques of dark channel prior and cloud processing are combined into the framework of pipeline image haze removal system. In the system, including the user management module, system sitting module, cloud-based image management module and image processing module, we transmit the image data with the secure cloud data control mechanism, and remove the haze in each image using dark channel prior. The experimental results show that the system has good effects on haze removal of pipe images, especially for the larger reflection area. The system can be applied to engineering practice.