Synthesis of True Color Images from the Fengyun Advanced Geostationary Radiation Imager

• 作者: Yuchen XIE Xiuzhen HAN Shanyou ZHU
• 来源期刊: 气象学报（英文版）
• 年，卷（期）: 2021,（6）
• 所属期刊栏目: ORIGINAL PAPER
• 页码范围: 1136-1147
• 页数: 12页
• 语种: 英文

摘要

The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Ad-vanced Geostationary Radiation Imager(AGRI)onboard China's Fengyun-4(FY-4)series of geostationary satellites only has blue and red bands,and we therefore have to synthesize a green band to produce RGB true color images.We used random forest regression and conditional generative adversarial networks to train the green band model using Himawari-8 Advanced Himawari Imager data.The model was then used to simulate the green channel reflectance of the FY-4 AGRI.A single-scattering radiative transfer model was used to eliminate the contribution of Rayleigh scat-tering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The condi-tional generative adversarial network model was better than random forest regression for the green band model in terms of statistical significance(e.g.,a higher determination coefficient,peak signal-to-noise ratio,and structural sim-ilarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scat-tering,and the images were able to show natural phenomena more vividly.The AGRI true color images could be used to monitor dust storms,forest fires,typhoons,volcanic eruptions,and other natural events.