IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2022)

Feasibility Study for an Ice-Based Image Monitoring System for Polar Regions Using Improved Visual Enhancement Algorithms

  • Yuchen Wang,
  • Yinke Dou,
  • Jingxue Guo,
  • Zhe Yang,
  • Bo Yang,
  • Yang Sun,
  • Weixin Liu

DOI
https://doi.org/10.1109/JSTARS.2022.3173821
Journal volume & issue
Vol. 15
pp. 3788 – 3799

Abstract

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Melting and evolution of Arctic Ocean sea ice in summer are one of the main factors affecting sea ice albedo and climate. At present, remote sensing images of sea ice are mainly acquired with the help of payload platforms, such as aircraft or satellites. The above methods have a large measurement scale and a short period. Sea ice research also requires suitable equipment for fine-scale, visualized long-term tracking observations of target sea ice regions. This article investigates the feasibility of measuring interannual variability in sea ice morphology in the Arctic sea ice environment using a low-power gimbal camera automated by satellite communications. Year-round observational data from the arctic field were used. The sea ice images were defogged and edge-enhanced by a newly developed algorithm with the help of human visual enhancement principles. During the 11th Chinese National Arctic Science Expedition, the system was placed on perennial ice in the northern Beaufort Basin to monitor sea ice appearance changes and the external state of the ice mass balance buoy. The system fuses visually enhanced sea ice images with ice balance buoy data from the same ice floe in a multi-scale environmental sequence to obtain sea ice observations with image sequences. The data complement the need for long-duration, fixed-ice, and short-visual-range observations in sea-ice studies. The equipment design methods and image processing algorithms involved in the experimental process have accumulated engineering experience for this application area. The research methodology provides a new framework for long-term, and visualized sea ice observation methods.

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