An improved neighborhood-based ratio approach for change detection in SAR images

The speckle noise of synthetic aperture radar (SAR) images limits its application in change detection. Compared with improved ratio (IR) and log-ratio (LR) operators, the neighborhood-based ratio (NR) technique can restrain the influence of speckle noise and is more suitable for change detection in...

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Bibliographic Details
Main Authors: Huifu Zhuang, Hongdong Fan, Kazhong Deng, Yang Yu
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:European Journal of Remote Sensing
Subjects:
Online Access:http://dx.doi.org/10.1080/22797254.2018.1482523
Description
Summary:The speckle noise of synthetic aperture radar (SAR) images limits its application in change detection. Compared with improved ratio (IR) and log-ratio (LR) operators, the neighborhood-based ratio (NR) technique can restrain the influence of speckle noise and is more suitable for change detection in SAR images. However, we find three drawbacks of NR by analyzing this method carefully. To overcome these defects, we propose an improved neighborhood-based ratio (INR) approach for change detection in SAR images. INR restructures the NR operator to exploit the neighborhood information more reasonably and is expected to reduce the impact of speckle noise better. IR, LR, mean ratio operator, NR, and INR are tested on two data sets to compare their performances in change detection of SAR images. Experimental results show that the proposed method can obtain better difference image than other state-of-art methods and improve the accuracy of change detection in SAR images effectively.
ISSN:2279-7254