SAR image despeckling algorithm using enhanced edge detection in bandelet domain

Zhihui Xin; Mengting Yuan; Zhixu Wang; Yu Sun; Jiayu Xuan; Wei Ma; Yongxin Li

doi:10.1117/12.2620741

8 July 2022 SAR image despeckling algorithm using enhanced edge detection in bandelet domain

Zhihui Xin, Mengting Yuan, Zhixu Wang, Yu Sun, Jiayu Xuan, Wei Ma, Yongxin Li

Proceedings Volume 12281, 2021 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology; 122810I (2022) https://doi.org/10.1117/12.2620741
Event: 2021 International Conference on Optical Instruments and Technology, 2022, Online Only

Abstract

With all-weather, all-time imaging characteristics of synthetic aperture radar (SAR), SAR image is applied widely. However, because of the SAR imaging mechanism, speckle noise is inevitably present in SAR images. In the translationinvariant second-generation bandelet transform (TIBT) domain, SAR image despeckling algorithm using edge detection and feature clustering (CFCM-TIBT) combines edge detection and fuzzy C-main clustering (FCM) operation is an efficient way to reduce speckle noise. However, the edges will be blurred by the algorithm. In order to improve the edge preservation ability and reduce false edge phenomenon. A new algorithm, named enhanced edge detection for SAR images despeckling in TIBT domain (CRFCM-TIBT), is proposed in this letter. It combines CFCM-TIBT and an improved edge detector, named C-RBED, which consists of Canny edge detector and rate-based edge detector (RBED). CRFCM-TIBT better realizes the extraction and separation of details that benefits from the ability of eliminating false edge pixels of C-RBED. The process of CRFCM-TIBT: C-RBED is first utilized to calculate and compare edge direction map (EDM) and edge strong map (ESM) several times. Then, TIBT and FCM are used to decompose and despeckle the edge-removed image, respectively. Finally, add the removed edges to the reconstructed image. In the two scenarios of Bedfordshire and Horse track, the Equivalent Look Number (ENL) and Edge Preservation Index (ESI) of this algorithm are better than traditional Lee filtering, FCM-TIBT and CFCM-TIBT. The experimental results show from the evaluation indicators and visual effects that the method proposed in this paper significantly improves ESI while ensuring a better ENL.

Citation Download Citation

Zhihui Xin, Mengting Yuan, Zhixu Wang, Yu Sun, Jiayu Xuan, Wei Ma, and Yongxin Li "SAR image despeckling algorithm using enhanced edge detection in bandelet domain", Proc. SPIE 12281, 2021 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology, 122810I (8 July 2022); https://doi.org/10.1117/12.2620741

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Synthetic aperture radar

Detection and tracking algorithms

Edge detection

Sensors

Image enhancement

Image filtering

Speckle

Show All Keywords

Keywords/Phrases

Search In:

Publication Years