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

作　　者：Yuchen XIE Xiuzhen HAN Shanyou ZHU 

机构地区：[1]School of Remote Sensing&Geomatics Engineering,Nanjing University of Information Science&Technology,Nanjing 210044 [2]National Satellite Meteorological Center,China Meteorological Administration,Beijing 100081

出　　处：《Journal of Meteorological Research》2021年第6期1136-1147,共12页气象学报（英文版）

基　　金：Supported by the National Key Research and Development Program of China(2018YFC150650);National Satellite Meteorological Center Mountain Flood Geological Disaster Prevention Meteorological Guarantee Project 2020 Construction Project(IN_JS_202004)。

摘　　要：The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced 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 scattering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The conditional 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 similarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scattering,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.

关 键 词：Advanced Geostationary Radiation Imager(AGRI) RGB true color random forest regression conditional generative adversarial networks Rayleigh scattering 

分 类 号：P414.4[天文地球—大气科学及气象学] V474.24[航空宇航科学与技术—飞行器设计]