| The absorption and scattering of solar radiation by atmospheric molecules and aerosol particles will cause the visible and near-infrared(VNIR)satellite images to become blurred and low-contrast,and also cause the apparent reflectance of each pixel in the satellite image to deviate from its true reflectance on the earth surface.Research on atmospheric correction technology is essential to improve the quality of remote sensing images and accurately obtain information on earth resources such as surface radiation budgets,biophysical and chemical parameters,and water cycles.Based on the characteristics of sub-meter spatial resolution optical satellite images,this dissertation analyzes the influence of atmospheric absorption,atmospheric path radiation and adjacency effect on atmospheric correction.Based on the above analysis results,an adaptive atmospheric correction algorithm is proposed.For the VNIR satellite images,atmospheric correction mainly includes atmospheric absorption correction,atmospheric path radiance correction and adjacency effect correction.The essence of atmospheric absorption correction is to calculate the total absorption transmittance of the atmospheric particles to solar radiation on the solar radiation transmission path.The simulation analysis results show that the key to improving the accuracy of atmospheric absorption correction is to obtain the atmospheric water vapor and ozone content which is time-space synchronized with satellite image.The atmospheric path radiation correction is essentially to calculate the atmospheric path radiation value.At present,the dark pixel method or the radiation transfer equation method is mainly used to obtain the atmospheric path radiation value corresponding to each pixel in the satellite image.The simulation analysis results show that the key to improving the accuracy of atmospheric path radiation correction is to obtain the atmospheric aerosol types and aerosol optical depth which is time-space synchronized with satellite image.The adjacency effect correction aims at solve the average background reflectance(ABR)of each pixel in the satellite image.Therefore,the key to the adjacency effect correction is to determine the value of the adjacency effect range and the contribution factor(or weight value)of the background pixel in this range to the ABR.However,there is currently a lack of systematic and comprehensive analysis of the related influence factors of the adjacency effect range and the contribution weight value of each background pixel to the ABR.Therefore,this dissertation systematically analyzes the related influence factors of adjacency effect correction through theoretical analysis and simulation data.The analysis results show that the smaller the observation wavelength,the higher the spatial resolution,the smaller the observation zenith angle,the higher the altitude of the target on the surface of the earth,the lower the height of the atmospheric molecular scattering layer,the lower the height of the aerosol scattering layer,the greater the optical thickness of atmospheric molecules and the greater the aerosol optical thickness,the smaller the effective adjacency effect range value.The greater the optical thickness of atmospheric molecules,the greater the aerosol optical thickness,the smaller the spatial distance between the background pixel and the target pixel and the greater the reflectance difference between the background pixel reflectance and the target pixel reflectance,the greater the contribution factor(or weight value)of the background pixel to the ABR.The large reflectance difference of adjacent ground objects in sub-meter spatial resolution optical satellite images is a major factor leading to serious adjacency effects.However,the traditional atmospheric correction algorithms do not consider the effect of RDCS on the ABR.These algorithms become inappropriate to correct the adjacency effect in SM satellite images.In this dissertation,for the first time,the influence of the reflectance difference between the background pixel and target pixel on the contribution weight values of the adjacency effect is considered.And the simulation analysis results show that the ratio of the radiance of the background pixel at the entrance pupil of the satellite to the radiance of the target pixel at the entrance pupil of the satellite(Lback/Ltarget)can quantitatively represent the relative magnitude of the contribution weight value of RDCS to the ABR.Based on this situation,we combine the value of Lback/Ltarget with the ABR expression in the 6S-AC to obtain the equivalent average background reflectance(EABR)expression,and replace ABR in the formula of the 6S-AC with EABR.The EABR depends on the the atmospheric molecules optical thickness,aerosol optical thickness,the spatial distance from the central pixel to its surrounding pixels(SDCS),and RDCS.The advantage of EABR over ABR is that the former considers contributions from the the atmospheric molecules optical thickness,aerosol optical thickness,SDCS,and RDCS to the adjacency effect.EABR can better represent the adjacency effect in the SM satellite image.Here,we develop an adaptive atmospheric correction algorithm(adaptive-AC)based on EABR to perform atmospheric correction on SM satellite images.Adaptive-AC can adjust the contribution factor(or weight value)of the background pixel to the adjacency effect according to the atmospheric molecules optical thickness,aerosol optical thickness,SDCS,and RDCS.The application of adaptive-AC to WorldView-3 panchromatic band satellite imagery(spatial resolution of 0.31 m)and GF-2 panchromatic band satellite imagery(spatial resolution of 0.81 m)eveals that adaptive-AC can significantly improve image quality,with the reflectance of pixels in the corrected image processed by adaptive-AC being close to the actual reflectance.The results show that the correction results of Adaptive-AC are better than those of 6S-AC and MODTRAN-AC.Taking the GF2 panchromatic satellite image of the Songshan calibration field on March 20,2020 as an example,the ground synchronous measured reflectance value of the high reflectance target area is 0.4756,and the ground synchronous measured reflectance value of the low reflectance target area is 0.0681.When the adjacency effect range value is 1920 meters,the average reflectance of each target area in the satellite image corrected based on Adaptive-AC(abbreviated as "Adaptive-AC true surface reflectance image")is very close to the average reflectance measured on the ground.The average reflectance of the high reflectance target area in the Adaptive-AC true surface reflectance image is 0.4406,and the average reflectance of the low reflectance target area is 0.0805;The average reflectance of each target area in the satellite image corrected based on the 6S-AC(abbreviated as "6S-AC true surface reflectance image")is quite different from the average reflectance measured on the ground.The average reflectance of the high reflectance target area in the 6S-AC true surface reflectance image is 0.3913,and the average reflectance of the low reflectance target area is 0.1004;The average reflectance of each target area in the satellite image corrected based on the MODTRAN-AC(abbreviated as " MODTRAN-AC true surface reflectance image”)is higher than the reflectance measured on the ground.The average reflectance of the high reflectance target area in the MODTRAN-AC true surface reflectance image is 0.4880,and the average reflectance of the low reflectance target area is 0.1211.Comparing the correction results of Adaptive-AC with the results of conventional image processing indicates that conventional image processing methods will bring noise and over-enhancement problems when improving the quality of satellite images,while Adaptive-AC will not bring noises and over-enhancement problems when improving the quality of satellite images.Taking the WV-3 panchromatic satellite image of the area near the Wanquan River Bridge in Beijing on April 1,2018 as an example,the roof sunroof of a large vehicle can be directly visually interpreted from the satellite image corrected based on Adaptive-AC.However,the information cannot be visually interpreted from the satellite image after conventional image processing.In general,that compared with ABR,EABR can better describe the essential characteristics of the adjacency effect,and the proposed corresponding adaptive-AC can well remove the effect of the atmosphere and surrounding environment from an SM satellite image,to restore the authenticity of the satellite imaging process,and improve the image quality and quantitative remote sensing accuracy of SM satellite image.Adaptive-AC is more suitable for SM satellite image preprocessing than 6S-AC and MODTRAN-AC approaches. |
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