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Abstract
Aiming at solving the degradation problem of Luojia 1-01 night-light remote sensing images, the main reason for the “glow” phenomenon was analyzed. The APSF (Atmospheric Point Spread Function) template of night-light image was obtained from atmospheric source scattering. The template was used as the initial value in the regularization restoration model in this paper. Experiments were carried out using single point and regional images. The results demonstrate that the estimated APSF and restoration results of the method are better than those from other methods, and the image quality is improved after restoration.
Highlights
With the continuous development of remote sensing technology, different types of remote sensing data are becoming more and more abundant
The APSF estimation method and ratio sparse constraint restoration model were proposed aiming at problems of the fuzzy quality reduction and noise in night-light images of Luojia 1-01
As long as we find an approximate point ground caused by the scattering of an isolated point light source through the atmosphere
Summary
With the continuous development of remote sensing technology, different types of remote sensing data are becoming more and more abundant. The identifiable approximate point features are obvious, such as independent ships or large landmark buildings These isolated point sources provide good data conditions for APSF estimation of night-light images. According to the image degradation and restoration model, restoration can achieve the effect of denoising and improving quality It can provide more accurate data as a basis for estimating socio-economic indicators. The APSF estimation method and ratio sparse constraint restoration model were proposed aiming at problems of the fuzzy quality reduction and noise in night-light images of Luojia 1-01. There is some noise in night-light images, so we proposed to further optimize the APSF value by adopting the ratio sparse constraint restoration model and reduce the noise in images
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