The presence of thin cloud in remote sensing images has brought great impact for follow-up image interpretation.An novel algorithm was proposed to remove the thin cloud from remote sensing images based on the theory of High-dimensional space geometrical informatics(HDSGI).One Image is mapped into an original point (vector) of a high-dimensional space by the theory of HDSGI

namely

a remote sensing image including of cloud is an point of high-dimensional space.In this new algorithm

through homomorphic filter

this high-dimensional space point is geometrically decomposed into two individual sub-spaces of different scales

decomposition components is done "restraining＼enhancing transformation" separately

the transformed sub-space components had been maken final synthesis be the required remote sensing image without the cloud.Using by actual satellite image and aviation image

experimental results have shown that the algorithm can not only remove the noisy of cloud but also is efficient for enhancing the edge information contrasting to the homomorphic filter and wavelet transform algorithms.