Power Generation Technology ›› 2020, Vol. 41 ›› Issue (6): 608-616.DOI: 10.12096/j.2096-4528.pgt.20006

• New and Renewable Energy • Previous Articles     Next Articles

Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm

Sha LIU1,3(), Zhe SUN2(), Zifeng QIU1,3,*(), Yan HU3()   

  1. 1 The 54 th Research Institute of CETC, Shijiazhuang 050081, Hebei Province, China
    2 Military Representatives Office of NED in Handan, Shijiazhuang 050081, Hebei Province, China
    3 Key Laboratory of Aerospace Information Applications of CETC, Shijiazhuang 050081, Hebei Province, China
  • Received:2020-03-17 Published:2020-12-31 Online:2021-01-12
  • Contact: Zifeng QIU
  • Supported by:
    National Key Research & Development Program of China(2017YFB0503003)

Abstract:

In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles, a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging, the prior law of dark channel, homogeneous filtering and SLIC algorithm, the influence of white area and uneven light in power inspection image was improved, the efficiency of UAV image dehazing was improved, and the adaptive calculation of atmospheric light intensity parameters was carried out to prevent the distortion in the dehazing process. The experimental results show that the algorithm can effectively restore the original details of the power inspection image. Through the comparison of subjective visual evaluation and fusion of a variety of objective evaluation indexes, it shows the superiority of the algorithm compared with the traditional algorithms.

Key words: wind farm, power inspection, image dehazing, homogeneous filtering, simple linear iterative clustering (SLIC)

CLC Number: