An Over-Complete Dictionary Design Based on GSR for SAR Image Despeckling

作者：Liu, Su; Zhang, Gong^*; Soon, Yeo Tat

来源：IEEE Geoscience and Remote Sensing Letters, 2017, 14(12): 2230-2234.

DOI：10.1109/LGRS.2017.2758397

• Despeckling
• dictionary design
• group sparse representation (GSR)
• synthetic aperture radar (SAR)

In this letter, we explore the concept of group sparse representation (GSR) to exploit the intrinsic structure of synthetic aperture radar (SAR) image. Noting that dictionary design is a crucial factor in GSR performance, we propose an over-complete dictionary to better fit the SAR image despeckling problem. This over-complete dictionary consists of the prespecified dictionaries and learned dictionary. Different kinds of dictionaries emulate the image from different angles. In this way, we can simultaneously obtain better performance on speckle noise suppression and image detail preservation. The experimental results on real SAR images demonstrate that the proposed over-complete dictionary based on GSR can achieve more effective speckle reduction as well as image detail preservation.

• 出版日期2017-12
• 单位南京航空航天大学