An Iterable Multidirectional Autocorrelation Approach forAerial Power Line Image Enhancement

A power line image photographed by UAV(unmanned aerial vehicle) has usually a complex background, wherein the thin power lines are so weak that the target lines detection rate is low. To solve this problem, an iterable multidirectional autocorrelation(IMA) approach is proposed to enhance image. Firstly, an effective filtering template is designed according to the local grey level distribution along longitudinal and lateral directions of a power line in a UAV aerial image, and the results of the directional filtering are used to perform an autocorrelational enhancement. The autocorrelational enhancement can be performed iteratively to get a satisfactory image enhancement result. Image enhancement results of IMA are compared with those of Canny, Hessian approaches in a series of experiments. Experiments results show that the proposed IMA approach is more suitable for UAV aerial image enhancement than Canny and Hessian approaches. The IMA approach is fast, and it can weaken complex background in aerial image dramatically while enhancing power line targets, which effectively improves recognition rate of power line targets in images.