Gradient Based SAR Image Despeckling and Super Resolution Using Zernike Moments and Bootstrapping

被引:0
作者
Arianpour, Yaser [1 ]
Amindavar, Hamidreza [2 ]
Ritcey, James A. [3 ]
机构
[1] Islamic Azad Univ, South Tehran Branch, Elect Engn Dept, Tehran, Iran
[2] Amirkabir Univ Technol, Elect Engn Dept, Tehran, Iran
[3] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
来源
2017 IEEE RADAR CONFERENCE (RADARCONF) | 2017年
关键词
SAR Despeckling; Super Resolution; gradient field; Zernike moment; Bootstrapping method;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a new despeckling and super resolution (SR) approach for synthetic aperture radar (SAR) applications. In our method, we transfers the speckled low resolution SAR image to gradient domain and extract all of edges with their sharpness. Then, using Zernike Moments and also Bootstrapping approach we obtains the new values for edges sharpness. By these new edges sharpness and after using the modified gradient field transformation, image reconstruction leads to noise-free high resolution images with better quality than traditional methods.
引用
收藏
页码:1634 / 1639
页数:6
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