Object Detection from SAR Images based on Curvelet Despeckling

被引：7

作者：

Devapal, Devi ^{[1
]}

Hashna, N. ^{[1
]}

Aparna, V. P. ^{[1
]}

Bhavyasree, C. ^{[1
]}

Mathai, Jeena ^{[1
]}

Soman, Sangeetha K. ^{[1
]}

机构：

[1] Coll Engn, Dept Comp Sci & Engn, Elikkattoor PO, Kollam 689696, Kerala, India

来源：

MATERIALS TODAY-PROCEEDINGS | 2019年 / 11卷

关键词：

SAR; Speckle; CA-CFAR; ENL; PSNR; SSIM; Curvelet;

D O I：

10.1016/j.matpr.2018.12.045

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

SAR images are increasingly gaining importance in the field of remote sensing applications. The receiving SAR data are affected by multiplicative speckle noise which form granular patterns. Hence despeckling is done prior to object detection. Here a comparison of several transform domain techniques are carried out for despeckling SAR images. Performance parameters such as ENL, PSNR, SSIM etc. are used to evaluate the result. From the result, Curvelet is chosen as the optimum technique for despeckling. In this paper Curvelet based despeckling of SAR images is performed and further object detection is done using CA-CFAR. (c) 2018 Elsevier Ltd. All rights reserved.

引用

页码：1102 / 1116

页数：15

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