Image compression and reconstruction of transmission line monitoring images using compressed sensing

• Published in: 2017 8th International Conference on Mechanical and Aerospace Engineering (ICMAE) pp. 371 - 375
• Main Authors: Liquan Zhao, Yulong Liu, Lin Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2017
• Subjects: Compressed sensing; generalized orthogonal matching pursuit; Image coding; image compression; Image reconstruction; Matching pursuit algorithms; Monitoring; Power transmission lines; Transmission line matrix methods
• ISBN: 1538633051; 9781538633052
• DOI: 10.1109/ICMAE.2017.8038674

In order to ensure safely and effective operation of the transmission line, the condition monitoring of transmission lines is widely applied to discover the dangerous points of transmission lines and monitor surrounding weather conditions. Since transmission lines run across fields, adopting mobile communication network to carry out the data transmission is very convenience. The operation cost is directly proportional to whose flow for data transmission. In order to reduce the operation cost, the compressed sensing technology is applied to image compression and image reconstruction in this paper. The proposed method uses sparse random matrix to sample transmission lines images on sensing nodes. Then reconstructing the image in the monitoring center using the generalized Orthogonal Matching Pursuit (gOMP) algorithm. The proposed method carries out the compression of image information transmitted under the precondition of ensuring the image quality, to reduce the data flow for image information, to further reduce the operation cost of the system.