摘要
针对合成孔径雷达(synthetic aperture radar,SAR)图像中乘性相干斑噪声的抑制与边缘保护问题,提出了一种基于非下采样轮廓波变换(NSCT)与自蛇扩散的抑斑新算法;该算法先利用NSCT变换对SAR图像进行多层子带分解;然后借助自蛇扩散对SAR图像不同子带分别实施参数不同的扩散滤波;最后对各去噪子带进行NSCT重构获得的SAR图像再次进行自蛇扩散滤波处理,从而实现带有边缘保护与增强的SAR图像相干斑抑制。实验表明,与多种传统抑斑算法相比,本文算法在相干斑抑制与边缘保护性能上均有明显提升。
Aiming at multiplicative speckle noise suppression and edge protection in synthetic aperture radar（ SAR） images,a new despeckling algorithm based on non-subsampled contourlet transform（ NSCT） and selfsnake diffusion is proposed. The SAR image is firstly decomposed into multilayer sub-bands by the NSCT. Then,different sub-bands are filtered by self-snake diffusions with different filtering parameters,respectively. The reconstructed SAR image is obtained by the inverse NSCT based on filtered sub-bands. In order to achieve well speckle reduction with edge protection and enhancement,the reconstructed SAR image is processed by self-snake diffusion again. The experimental results and comparisons with several traditional algorithms show that the proposed algorithm can significantly improve performances in speckle reduction and edge protection.
作者
潘杨
朱磊
胡晓
李楠
PAN Yang;ZHU Lei;HU Xiao;LI Nan(College of Electronics and Information, Xi＇an Polytechnic University, Xi＇an 710048, China)
出处
《科学技术与工程》
北大核心
2018年第13期79-85,共7页
Science Technology and Engineering
基金
国家自然科学基金(61401347)
陕西省科技厅工业科技攻关项目(2016GY-101)
陕西省教育厅自然科学基金(17JK0343)
西安工程大学博士科研启动基金(BS107020096)资助
