Remote sensing image registration method based on synchronous atmospheric correction

Abstract

Image registration is a crucial preprocessing step in remote sensing applications, integrating information from multiple images to achieve synergistic advantages. Nevertheless, aerosols characterized by spatiotemporal heterogeneity can result in the blurring of remote-sensing images, thereby compromising the accuracy of image registration. This paper begins by analyzing the basic principles of atmospheric correction and image registration. The variations in atmospheric radiative contribution caused by aerosol changes in real-world scenarios were simulated, along with an examination of the relationship between atmospheric effects and the quantity of image features. Subsequently, addressing the challenge posed by insufficient synchronicity in aerosol parameters and the influence of atmospheric effects on remote sensing image registration, we propose a registration method based on synchronous atmospheric correction. This approach utilizes the Airborne Synchronous Monitoring Atmospheric Corrector (ASMAC) to obtain aerosol optical depth and column water vapor images for synchronous atmospheric correction of remote sensing images, along with the assessment of the registration transformation matrix. Finally, airborne experiments involving ASMAC and high-resolution cameras are conducted to validate the proposed method's improvement in remote sensing image registration accuracy. Experimental results demonstrate the effectiveness of the proposed method, showcasing an increase in the number of features and improvements in quantitative evaluation metrics. Specifically, the normalized correlation coefficient improved by up to 2.408%, while the normalized mutual information increased by a maximum of 1.395%, a maximum feature count and successfully matched features improvement of 21.1% and 38.5%