所属单位：航天学院
发表刊物：Lect. Notes Electr. Eng.
摘要：A new synthetic aperture radar (SAR) image denoising method based on fast weighted nuclear norm minimization (FWNNM) is proposed. SAR image is firstly modelled by a logarithmic additive model for modelling of the speckle. Then, the non-local similarity is used for image block matching. Next, according to the framework of the low-rank model, randomized singular value decomposition (RSVD) is introduced to replace the singular value decomposition (SVD) in weighted nuclear norm minimization (WNNM) for approximating the low-rank matrix. Finally, the gradient histogram preservation (GHP) method is employed to enhance the texture of the image. Experiments on MSTAR database show that the proposed approach is effective in SAR image denoising and the edge preserving in comparison with some traditional algorithms. Moreover, it is three times faster than WNNM method. © 2020, Springer Nature Singapore Pte Ltd.
ISSN号：1876-1100
是否译文：否
发表时间：2020-01-01
合写作者：Zhao, Huanyue,Li, Xiaofei,Wang, Jianing,Liu, Chunsheng,Sheng, Yuebin,Huang, Panpan
通讯作者：王彩云
发表时间：2020-01-01