Title: Pipeline image haze removal system using dark channel prior on cloud processing platform

Authors: Ce Li; Tan He; Yingheng Wang; Liguo Zhang; Ruili Liu; Jing Zheng

Addresses: China University of Mining and Technology, 100083, Beijing, China; Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, 210094, Nanjing, China ' China University of Mining and Technology, 100083, Beijing, China; Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, 210094, Nanjing, China ' Tongji University, 201804, Shanghai, China ' Computer Science and Engineering, Harbin Engineering University, 150001, Harbin, China; Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong, China ' China University of Mining and Technology, 100083, Beijing, China ' China University of Mining and Technology, 100083, Beijing, China; Stanford University, 94305, Palo Alto, USA

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.

Keywords: pipeline image processing; dark channel prior; atmospheric optical; data access control.

DOI: 10.1504/IJCSE.2020.107254

International Journal of Computational Science and Engineering, 2020 Vol.22 No.1, pp.84 - 95

Received: 14 Mar 2019
Accepted: 25 May 2019

Published online: 04 May 2020 *

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