A Terrain Shading Correction Method for Visible Light Waveband of Remote Sensing Image

Abstract

The invention relates to a method for correcting terrain fall shadows in the visible light band of remote sensing images, which mainly includes image preprocessing, fall shadow extraction, SCS+C calculation, SEVI calculation, sample production, machine learning, terrain fall shadow correction, and terrain fall shadow correction effect evaluation . The invention can effectively eliminate the falling shadow interference in the red, green and blue bands of the remote sensing image, makes up for the deficiency that SEVI can only obtain single-band information that eliminates the falling shadow interference, and also makes up for the failure of the conventional DEM-based terrain correction method in the falling shadow insufficient.

Description

technical field [0001] The invention relates to the technical field of shading compensation, in particular to a method for correcting terrain fall shadows in the visible light band of remote sensing images. Background technique [0002] Terrain shading seriously interferes with the extraction accuracy of vegetation information in mountainous areas and causes great difficulties in the interpretation of land cover in mountainous areas. Therefore, it is of great significance to study compensation methods for spectral information of terrain shading. The current terrain shading correction methods mainly include mountainous radiative transfer models, empirical correction models based on DEM data, and band combination optimization calculation models. The method based on the mountain radiative transfer model considers direct solar radiation, atmospheric diffuse radiation, and surrounding terrain reflection radiation at the same time, and the effect is good, but the model parameters ...

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Problems solved by technology

The method based on the mountain radiative transfer model considers direct solar radiation, atmospheric diffuse radiation and surrounding terrain reflection radiation at the same time.

The empirical correction method based on DEM data is based on the statistical relationship between reflectance and cosi, including statistical-empirical model, normalization model, Lambertian body reflectivity model and non-Lambert body reflectivity model, but this type The method is only effective for the umbra, and the correction effect for the falling shadow is not good

The method based on the band combination optimization calculation model obtains the vegetation information after removing the influence of terrain by constructing a special vegetation index, such as band ratio model, FCD model and VBSI index, terrain-adjusted vegetation index, normalized difference mountain vegetation index, shadow Eliminate Vegetation Index (SEVI), etc. However, this type of model can only obtain the index information of falling shadows, and lacks multispectral information

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