Hyperspectral Remote Sensing Image Cloud Detection Based on Spectral Analysis and Dynamic Fractal Dimension

The rapid cloud detection method in various backgrounds is studied based on the spectral reflection characteristics. The spectral reflection characteristics are combined with the texture features of the clouds, and a comprehensive cloud detection algorithm is proposed based on the combination of dynamic fractal dimension and radiation quantity characteristics. The hyperspectral remote sensing images taken by the Hyperion sensor of the EO-1 satellite are taken as examples to study the cloud-containing remote sensing images of different underlying surfaces, and the thick clouds area and thin clouds area are detected and analyzed. Compared with the two algorithms of remote sensing image cloud detection, the proposed algorithm can identify the thin cloud regions more accurately, which can greatly improve the accuracy of remote sensing image cloud detection and at the same time can meet the requirements of fast cloud detection of satellite-borne hyperspectral images.