Journal of Marine Science and Engineering (Nov 2021)

Perceptual Fusion of Electronic Chart and Marine Radar Image

  • Chuang Zhang,
  • Meihan Fang,
  • Chunyu Yang,
  • Renhai Yu,
  • Tieshan Li

DOI
https://doi.org/10.3390/jmse9111245
Journal volume & issue
Vol. 9, no. 11
p. 1245

Abstract

Read online

Electronic charts and marine radars are indispensable equipment in ship navigation systems, and the fusion display of these two parts ensures that the vessel can display dangerous moving targets and various obstacles on the sea. To reduce the noise interference caused by external factors and hardware, a novel radar image denoising algorithm using the concept of Generative Adversarial Network (GAN) using Wasserstein distance is proposed. GAN focuses on transferring the image noise distribution between strong and weak noise, while the perceptual loss approach is to suppress the noise by comparing the perceptual characteristics of the output after denoising. Afterwards, an image registration method based on image transformation is proposed to eliminate the imaging difference between the radar image and chart image, in which the visual attribute transfer approach is used to transform images. Finally, the sparse theory is used to process the high frequency and low frequency subband coefficients of the detection image obtained by the fast Fourier transform in parallel to realizing the image fusion. The results show that the fused contour has a high consistency, fast training speed and short registration time.

Keywords