Sparse PDE for SAR image speckle suppression. Issue 6 (24th April 2017)

• Record Type: Journal Article
• Authors: Wang, Zelong; Tan, Xintong; Yu, Qi; Zhu, Jubo
• Is Part Of: IET image processing. Volume 11:Issue 6(2017)
• Page Start: 425
• Page End: 432
• Publication Date: 2017-04-24
• Subjects: synthetic aperture radar -- radar imaging -- partial differential equations -- image denoising -- statistical analysis; SAR image speckle suppression -- synthetic aperture radar -- noise removal -- imaging objects -- partial differential equation -- statistical property -- image denoising -- edge‐preserving -- line‐like objects -- point‐like objects -- scattering characters -- sparse PDE model -- numerical algorithm -- sparse constraint -- diffusion process; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2016.0769
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Speckle suppression is extremely important for understanding and utilising synthetic aperture radar (SAR) images, while the emphasis of the traditional methods for speckle suppression is usually focused on removing the noise instead of keeping the scattering character of imaging objects, which has caused serious interference to the subsequent applications of SAR images. The authors aim to develop sparse partial differential equation (PDE) for speckle suppression of SAR image, where the PDE model is associated with the sparse prior of objects and the statistical property of speckle. The PDE model has been proved to have the ability of denoising and edge‐preserving by proper design, and the sparse prior of the point‐ and line‐like objects on SAR images has been also illustrated, both of which help for keeping the scattering characters. To solve the proposed sparse PDE model, a numerical algorithm is designed and the sparse constraint is realised in each step of the diffusion process. In experiments, several real SAR images are utilised to validate the performance of the proposed method.