Remote sensing image stripe noise removal model based on detail infor-mation constraints
Remote sensing images are often contaminated by stripe noise during the acquisition process,which reduces the visu-al effect of remote sensing images and has an adverse effect on image interpretation and inversion.Although some mainstream stripe noise removal methods based on variational methods can remove stripe noise,they often lead to serious loss of image de-tail information.Based on the above problems,this paper proposes a remote sensing image stripe noise removal model DIS-UTV based on detail information constraint.In the DISUTV model,the proposed detail information separation operator based on bilateral filter and orthogonal subspace projection is effectively combined with one-way total variation regularization term,group sparsity regularization term and one-way total variation regularization constraint term,and the alternating direction mul-tiplier method is used to solve it,which is used to obtain high-precision stripe noise without detail information from stripe noise images.The stripe noise removal ability,detail information retention ability and robustness of the algorithm are verified using simulated data and real data,and compared with existing cutting-edge methods.Experimental results show that the proposed method can better retain the detail information of the image while removing stripe noise,and presents good qualitative and quantitative results.
stripe noise extractionorthogonal subspace projectiondetail information separation operatorone-way full varia-tional splittinggroup sparsity
NETL
NSTL
万方数据
