A New Algorithm of Cloud Removing for Optical Images Based on Wavelet Threshold Theory

Frequency relationships of wavelet coefficients describing sceneries and cloud in a single optical remote sensing image are analyzed after it is decomposed by wavelet transform.An algorithm of cloud threshold is proposed for removing cloud.Scenery information and cloud noises are distributed to coefficients of low levels and high levels respectively by choosing appropriate numbers of demarcation levels.Most of cloud noises and some scenery information are included in high level coefficients where cloud is brighter than scenery.Cloud can be removed from these coefficients and scenery information can be kept by setting a threshold with brightness.Weight factors are assigned to detail coefficients of low level,high level,and approximation coefficients respectively for enhancing the contrast of sceneries and decrease remaining cloud.The three parts of coefficients are reconstructed and fused to get processed result.Entropy is proposed to be a criterion to choose best demarcation level,weighted factor and threshold.It is proved that according to the entropy as a criterion these parameters can be chosen correctly by experiments.And the proposed algorithm is better than homomorphism filtering and Retinex algorithm.